U.S. patent application number 17/558864 was filed with the patent office on 2022-04-14 for method for identifying potential associates of at least one target person, and an identification device.
This patent application is currently assigned to NEC Corporation. The applicant listed for this patent is NEC Corporation. Invention is credited to Hong Yen ONG, Hui Lam ONG, Wei Jian PEH, Satoshi YAMAZAKI.
Application Number | 20220114826 17/558864 |
Document ID | / |
Family ID | |
Filed Date | 2022-04-14 |
United States Patent
Application |
20220114826 |
Kind Code |
A1 |
ONG; Hui Lam ; et
al. |
April 14, 2022 |
METHOD FOR IDENTIFYING POTENTIAL ASSOCIATES OF AT LEAST ONE TARGET
PERSON, AND AN IDENTIFICATION DEVICE
Abstract
There is provided a method for identifying potential associates
of at least one target person, the method comprising: providing a
plurality of videos; identifying appearances of the at least one
target person in the plurality of videos; establishing a plurality
of video scenes from the plurality of videos, wherein each one of
the plurality of video scenes begins at a first predetermined
duration before a first appearance of the at least one target
person in the respective video scene and ends at a second
predetermined duration after a last appearance of said at least one
target person in the respective video scene; determining
individuals who appear in more than a predetermined threshold
number of the plurality of video scenes; and identifying the
individuals as potential associates of the at least one target
person.
Inventors: |
ONG; Hui Lam; (Singapore,
SG) ; YAMAZAKI; Satoshi; (Singapore, SG) ;
PEH; Wei Jian; (Singapore, SG) ; ONG; Hong Yen;
(Singapore, SG) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
NEC Corporation |
Tokyo |
|
JP |
|
|
Assignee: |
NEC Corporation
Tokyo
JP
|
Appl. No.: |
17/558864 |
Filed: |
December 22, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16642279 |
Feb 26, 2020 |
11250251 |
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PCT/JP2019/032161 |
Aug 16, 2019 |
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17558864 |
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International
Class: |
G06V 40/10 20060101
G06V040/10; G06V 20/40 20060101 G06V020/40; G06V 20/52 20060101
G06V020/52; G06V 40/20 20060101 G06V040/20; G06V 40/16 20060101
G06V040/16 |
Foreign Application Data
Date |
Code |
Application Number |
Sep 6, 2018 |
SG |
10201807678W |
Claims
1. A method for identifying potential associates of at least one
target person, the method comprising: providing a plurality of
videos; identifying appearances of the at least one target person
in the plurality of videos; establishing a plurality of video
scenes from the plurality of videos, wherein each one of the
plurality of video scenes begins at a first predetermined duration
before a first appearance of the at least one target person in the
respective video scene and ends at a second predetermined duration
after a last appearance of said at least one target person in the
respective video scene; determining individuals who appear in more
than a predetermined threshold number of the plurality of video
scenes; and identifying the individuals as potential associates of
the at least one target person.
2. The method according to claim 1, wherein identifying the
appearances of a respective target person of the at least one
target person from the plurality of videos further comprises:
determining an attribute of the respective target person; and
identifying, from the plurality of videos, an individual possessing
the attribute as the respective target person.
3. The method according to claim 2, wherein the attribute further
comprises facial information of the respective target person.
4. The method according to claim 2, wherein the attribute further
comprises a physical characteristic of the respective target
person.
5. The method according to claim 2, wherein the attribute further
comprises a behavioural characteristic of the respective target
person.
6. The method according to claim 1, wherein any one of the
plurality of video scenes further comprises one or more camera
surveillance footage of a location.
7. The method according to claim 6, wherein each of the one or more
camera surveillance footage shows a different view of the
location.
8. An identification device configured to identify potential
associates of at least one target person, the identification device
comprising: at least one memory storing instructions, and at least
one processor configured to execute the instructions to; receive a
plurality of videos; identify appearances of the at least one
target person in the plurality of videos; establish a plurality of
video scenes from the plurality of videos, wherein each one of the
plurality of video scenes begins at a first predetermined duration
before a first appearance of the at least one target person in the
respective video scene and ends at a second predetermined duration
after a last appearance of said at least one target person in the
respective video scene; search for individuals who appear in the
plurality of video scenes; determine which of the individuals
appear in more than a predetermined threshold number of the
plurality of video scenes; and identify the individuals who appear
in more than a predetermined threshold number of the plurality of
video scenes as the potential associates of the at least one target
person.
9. The identification device according to claim 8, wherein the
processor configured to execute the instructions to; determine an
attribute of a respective target person of the at least one target
person; and identify, from the plurality of videos, an individual
possessing the attribute as the respective target person.
10. The identification device according to claim 9, wherein the
attribute further comprises facial information of the respective
target person.
11. The identification device according to claim 9, wherein the
attribute further comprises a physical characteristic of the
respective target person.
12. The identification device according to claim 9, wherein the
attribute further comprises a behavioural characteristic of the
respective target person.
13. The identification device according to claim 8, wherein any one
of the plurality of video scenes further comprises one or more
camera surveillance footage of a location.
14. The identification device according to claim 13, wherein each
of the one or more camera surveillance footage shows a different
view of the location.
15. A non-transitory computer readable medium having stored thereon
instructions which, when executed by a processor, make the
processor carry out a method for identifying potential associates
of at least one target person, the method comprising: receiving a
plurality of videos; identifying appearances of the at least one
target person in the plurality of videos; establishing a plurality
of video scenes from the plurality of videos, wherein each one of
the plurality of video scenes begins at a first predetermined
duration before a first appearance of the at least one target
person in the respective video scene and ends at a second
predetermined duration after a last appearance of said at least one
target person in the respective video scene; determining
individuals who appear in more than a threshold number of the
plurality of video scenes; and identifying the individuals as
potential associates of the at least one target person.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present application is a continuation application of
U.S. patent application Ser. No. 16/642,279 filed on Feb. 26, 2020,
which is a National Stage Entry of international application
PCT/JP2019/032161, filed on Aug. 16, 2019, which claims the benefit
of priority from Singaporean Patent Application 10201807678 W filed
on Sep. 6, 2018, the disclosures of all of which are incorporated
in their entirety by reference herein.
TECHNICAL FIELD
[0002] The present invention generally relates to methods for
identifying potential associates of at least one target person, and
identification devices.
BACKGROUND ART
[0003] An organized crime group can be defined as a group of people
working together on a continuing basis for coordination and
planning of criminal activities. Their group structures vary, often
consisting of a durable core of key individuals, cluster of
subordinates, specialists, and other more transient members, plus
an extended network of associates. Many such groups are often loose
networks of criminals that come together for a specific criminal
activity, acting in different roles depending on their skills and
expertise.
[0004] To discover an organized crime group network of associates,
apart from digital/cyberspace monitoring, the physical world's
video surveillance systems can be the extended eye of law
enforcement agencies to monitor and discover the potential network
of associates.
SUMMARY OF INVENTION
Solution to Problem
[0005] According to a first aspect, there is provided a method for
identifying potential associates of at least one target person, the
method comprising: providing a plurality of videos; identifying
appearances of the at least one target person in the plurality of
videos; establishing a plurality of video scenes from the plurality
of videos, wherein each one of the plurality of video scenes begins
at a first predetermined duration before a first appearance of the
at least one target person in the respective video scene and ends
at a second predetermined duration after a last appearance of said
at least one target person in the respective video scene;
determining individuals who appear in more than a threshold number
of the plurality of video scenes; and identifying the individuals
as potential associates of the at least one target person.
[0006] According to a second aspect, there is provided an
identification device configured to identify potential associates
of at least one target person, the identification device
comprising: a receiving module configured to receive a plurality of
videos; an appearance search module configured to identify
appearances of the at least one target person in the plurality of
videos; an appearance consolidator module configured to establish a
plurality of video scenes from the plurality of videos, wherein
each one of the plurality of video scenes begins at a first
predetermined duration before a first appearance of the at least
one target person in the respective video scene and ends at a
second predetermined duration after a last appearance of said at
least one target person in the respective video scene; a
co-appearance search module configured to search for individuals
who appear in the plurality of video scenes; an appearance analyzer
module configured to determine which of the individuals appear in
more than a predetermined threshold number of the plurality of
video scenes; and an output module configured to identify the
individuals who appear in more than a predetermined threshold
number of the plurality of video scenes as the potential associates
of the at least one target person.
[0007] According to a third aspect, there is provided a
non-transitory computer readable medium having stored thereon
instructions which, when executed by a processor, make the
processor carry out a method for identifying potential associates
of at least one target person, the method comprising: receiving a
plurality of videos; identifying appearances of the at least one
target person in the plurality of videos; establishing a plurality
of video scenes from the plurality of videos, wherein each one of
the plurality of video scenes begins at a first predetermined
duration before a first appearance of the at least one target
person in the respective video scene and ends at a second
predetermined duration after a last appearance of said at least one
target person in the respective video scene; determining
individuals who appear in more than a threshold number of the
plurality of video scenes; and identifying the individuals as
potential associates of the at least one target person.
BRIEF DESCRIPTION OF DRAWINGS
[0008] The accompanying figures, where like reference numerals
refer to identical or functionally similar elements throughout the
separate views and which together with the detailed description
below are incorporated in and form part of the specification, serve
to illustrate various embodiments and to explain various principles
and advantages in accordance with a present embodiment.
[0009] FIG. 1 shows a flow diagram illustrating a method for
identifying potential associates of at least one target person
according to various embodiments;
[0010] FIG. 2 shows an identification device for implementing the
method illustrated in FIG. 1, according to various embodiments;
[0011] FIG. 3 illustrates a video scene analysis for a single
location and a single target person according to various
embodiments;
[0012] FIG. 4 illustrates a video scene analysis for more than one
location and more than one target person according to various
embodiments;
[0013] FIG. 5 shows an illustration of how potential associates are
identified according to various embodiments; and
[0014] FIG. 6 depicts an exemplary device according to various
embodiments.
DESCRIPTION OF EMBODIMENTS
[0015] Various embodiments provide devices and methods for
identifying potential associates of at least one target person.
[0016] The physical world's video surveillance systems have long
been the extended eye of law enforcement agencies to monitor
criminal activities and discover the potential associates of
organized crime groups, apart from digital/cyber surveillance.
[0017] Video surveillance systems are usually built and deployed to
identify registered personnel, but some of the more advanced
surveillance system also has the ability to track and associate
people who are captured on camera together to build a registered
person connection network. Video surveillance systems are usually
built and deployed to identify specific targeted persons, but some
of the more advanced surveillance systems also have the ability to
track and associate people that are seen together with them to
build a registered person connection network.
[0018] These existing solutions might be useful, but are limited to
or are more suitable to discover the relation link among family
members as well as friends and colleagues. Such solutions will also
fail to discover hidden associates of a target person, especially
in situations where the target person and his associates are not
captured on camera together. For example, organized crime group's
key individuals and their extended network of associates tend to
stay off the grid and avoid being seen together to hide their
connection during planning or execution of criminal activities.
Most of them try to avoid communication through phone, emails,
social networks (facebook, linkedin, etc) and instant messengers
(whatsapp, line, wechat, etc) where there is a possibility to
obtain the communication evidence through digital tracing by
authorized law enforcers.
[0019] Further, some organized crime group members might make
indirect contact or exchange information with their extended
network of associates in crowded public areas that make it easier
to cover their tracks and appearance. There is no surprise that
some associates might not even know who they are communicating
with. For instance, a first associate may be required to retrieve a
physical object left in a public location by a second associate. By
the time the first associate arrives at the designated public
location to retrieve the object, the second associate may already
have left. Even with a video surveillance system installed to
monitor the location, both associates will not be caught on camera
together since there is no direct communication between them.
[0020] As a result of such careful ways of communication, there is
difficulty for law enforcers to monitor and discover associates of
such organized crime groups.
[0021] Hence, there exists a need to provide a solution to the
above-mentioned problem.
[0022] The present invention provides a solution to the
above-mentioned problem. During analysis of videos captured by
surveillance cameras to identify possible associates of a target
person, by extending the analysis range to include a period of time
before a first appearance of the target person at a location
captured by the surveillance cameras and another period of time
after a last appearance of the target person at the same location,
it is possible to discover unknown associates of the target
person.
[0023] The results are further improved when videos of more than
one target persons who belong to a same group are analysed. For
example, if an unknown individual is found to appear in more than a
threshold number of the videos, the probability that the unknown
individual is an associate of the target persons is higher.
[0024] Advantageously, the present invention allows identification
of potential associates of a target person, even if they are not
co-appearing together in the videos.
[0025] Advantageously, the probability that the identified
potential associates are indeed associates of the target person is
increased when videos of more than one target persons are
analysed.
[0026] FIG. 1 shows a flow chart illustrating a method for
identifying potential associates of at least one target person. In
102, a plurality of videos is provided. The plurality of videos may
be video recordings of locations captured by surveillance cameras,
hand phone cameras, CCTV (closed-circuit television) cameras,
web-cams or other similar devices. The locations may be places
where the at least one target person has been seen, known to have
been to or frequented, or suspected locations where the at least
one target person provides or receives information to or from
associates of the same criminal group. The plurality of videos may
be in a file format such as mp4, avi, mkv, wmv, mov or other
similar video format. Further, each of the plurality of videos may
indicate a time, date and location at which each respective video
is recorded. In an embodiment, the plurality of videos may be
processed into an entry database consisting of one or more entries,
wherein each of the one or more entries represents an appearance of
a person at a time, date and location in the plurality of videos,
wherein each of the one or more entries indicates an attribute of
the person.
[0027] In 104, appearances of the at least one target person in the
plurality of videos are identified. This identification process may
be achieved by determining an attribute of the respective target
person, and then identifying, from the plurality of videos, an
individual possessing the attribute as the respective target
person. For example, the attribute may be facial information of the
at least one target person which may be determined from a picture
of the at least one target person's face. The attribute may also be
a physical characteristic of the at least one target person, for
example height, body size, hair colour, skin colour, other physical
features or combinations thereof of such features that may be used
to identify the at least one target person from the plurality of
videos. The attribute may also be a behavioural characteristic of
the at least one target person such as, for example, the way the at
least one target person walks, stands, moves, talks, other similar
characteristics or combinations thereof that may be used to
identify the target person from the plurality of videos.
[0028] In 106, a plurality of video scenes is established from the
plurality of videos, wherein each one of the plurality of video
scenes begins at a first predetermined duration before a first
appearance of the at least one target person in the respective
video scene and ends at a second predetermined duration after a
last appearance of said at least one target person in the
respective video scene. Each of the plurality of video scenes may
comprise surveillance footage of a location where at least one
appearance of the targeted person is identified. Practically, most
locations would typically have more than one surveillance camera
installed to monitor the respective locations, such that each of
these surveillance cameras may either provide surveillance for
different parts of the location, or monitor the location from
different views or angles. Therefore, each of the plurality of
video scenes may further comprise one or more camera surveillance
footages of a respective location where at least one appearance of
the respective target person is identified. Advantageously, taking
into consideration all available surveillance footages of a
location can cover scenarios in which the target person is at a
spot where only one of the surveillance cameras can capture the
person on video.
[0029] Further, each of the plurality of video scenes is
established such that each video scene begins at a first
predetermined duration before a first identified appearance of the
at least one target person, and ends at a second predetermined
duration after a last appearance of the at least one target person.
For example, where a first and a last appearance of a target person
at a location is at 2 pm and 3 pm on a same date respectively with
intermediate appearances at 2.10 pm, 2.25 pm, 2.40 pm and 2.50 pm,
and the first and second predetermined duration are set as 20
minutes and 25 minutes respectively, then the resulting video scene
will begin at 1.40 pm and end at 3.25 pm on the same date.
[0030] In 108, individuals who appear in more than a predetermined
threshold number of the plurality of video scenes are determined.
The individuals refer to all other persons besides the at least one
target person who appear in the plurality of video scenes. These
individuals do not need to be seen communicating with the at least
one target person in the plurality of video scenes in order to be
considered as potential associates, as long as they are found to
appear in more than a predetermined threshold number of video
scenes. The predetermined threshold number may be determined by
trial and error, and may vary depending on the quantity or quality
of videos to be analysed. Appearances of each individual may be
identified based on a determined attribute of the respective
individual, such as facial information, physical characteristics,
behaviour characteristics or other attributes that may be used to
identify the individual.
[0031] In 110, the individuals who appear in more than the
predetermined threshold number of the video scenes are identified
as potential associates of the at least one target person.
[0032] FIG. 2 shows an identification device 200 configured to
implement the method illustrated in FIG. 1. The device 200 includes
a receiving module 202, an appearance search module 204, a
consolidator module 206, a co-appearance search module 208, an
analyser module 210 and an output module 212.
[0033] The receiving module 202 is configured to receive a
plurality of videos. The plurality of videos may be video
recordings of locations captured by surveillance cameras, hand
phone cameras, CCTV (closed-circuit television) cameras, web-cams
or other similar devices. The locations may be places where the at
least one target person has been seen, known to have been to or
frequented, or suspected locations where the at least one target
person provides or receives information to or from associates of
the same criminal group. The plurality of videos may be in a file
format such as mp4, avi, mkv, wmv, mov or other similar video
format. Further, each of the plurality of videos may indicate a
time, date and location at which each respective video is
recorded.
[0034] The appearance search module 204 is configured to identify
appearances of the at least one target person in the plurality of
videos. In an embodiment, the appearance search module 204 may be
further configured to determine an attribute of a respective target
person of the at least one target person and identify, from the
plurality of videos, an individual possessing the attribute as the
respective target person. For example, the attribute may comprise
facial information, a physical characteristic or a behavioural
characteristic of the respective target person.
[0035] The appearance consolidator module 206 is configured to
establish a plurality of video scenes from the plurality of videos,
wherein each one of the plurality of video scenes begins at a first
predetermined duration before a first appearance of the at least
one target person in the respective video scene and ends at a
second predetermined duration after a last appearance of said at
least one target person in the respective video scene. In an
embodiment, the plurality of video scenes may further comprise one
or more camera surveillance footage of a location. Further, each of
the one or more camera surveillance footages may show a different
view of the location.
[0036] The co-appearance search module 208 is configured to search
for individuals who appear in the plurality of video scenes. In an
embodiment, appearances of each individual may be identified based
on a determined attribute of the respective individual, such as
facial information, physical characteristics, behaviour
characteristics or other attributes that may be used to identify
the individual.
[0037] The appearance analyzer module 210 is configured to
determine which of the individuals appear in more than a
predetermined threshold number of the plurality of video scenes.
The output module 212 is configured to identify the individuals who
appear in more than a predetermined threshold number of the
plurality of video scenes as the potential associates of the at
least one target person.
[0038] FIG. 3 illustrates a video scene analysis for a single
location and a single target person according to various
embodiments. A video scene 300 comprises video footage from one or
more surveillance cameras of a single location at a particular
date. In this embodiment, a first appearance of a target person 302
occurs at 2145 hours and a last appearance of the target person
occurs at 2148 hours. Further, a first predetermined duration and a
second predetermined duration are both set as 5 minutes.
Accordingly, the video scene 300 begins at the first predetermined
duration before the first appearance of the target person, which is
at 2140 hours, and ends at the second predetermined duration after
the last appearance of the target person, which is 2153 hours.
Further, the video scene 300 may not require a continuous presence
of the target person 302. For example, the target person 302 is not
present for 2 minutes between 2146 hours and 2148 hours in the
video scene 300. Since the 2 minute absence of the target person
302 is shorter than the second predetermined duration of 5 minutes,
the appearance of the target person 302 at 2146 hours is not
considered as the last appearance. Therefore, the period of time
from 2145 hours to 2148 hours of video scene 300 comprises one
logical appearance of the target person 302.
[0039] In an embodiment, there may be a third predetermined
duration for limiting a duration of each time that a target person
can be absent in a video scene. Referring to video scene 300, a
third predetermined duration may be set as, for example, 20
minutes. This means that a maximum duration for each time that the
target person 302 can be absent in the video scene 300 is 20
minutes. In the video scene 300, the target person 302 is not
present for 2 minutes between 2146 hours and 2148 hours. Since the
2 minute absence of the target person 302 is shorter than the third
predetermined duration of 20 minutes, the appearance of the target
person 302 at 2146 hours is not considered as a last appearance.
Therefore, the period of time from 2145 hours to 2148 hours of
video scene 300 comprises one logical appearance of the target
person 302. If, for example, the period of absence starting from
2147 hours of the target person 302 exceeds the third predetermined
duration, the video scene 300 will instead end at the second
predetermined duration of 5 minutes after 2147 hours, at 2152
hours. Further, if the target person 302 then reappears in the
plurality of videos after 2152 hours, for example at 2230 hours, a
new video scene will be established starting at the first
predetermined duration of 5 minutes before 2230 hours, at 2225
hours. In this case, the period of time from 2145 hours to 2147
hours comprises one logical appearance of the target person 302,
and the period of time that starts at 2230 hours until a next last
appearance of the target person 302 comprises another logical
appearance of the target person 302. It will be appreciated that
the first, second and third predetermined duration may be set to
any duration that may be deemed suitable for analysis of the video
scenes.
[0040] Next, individuals other than the target person 302 are
identified. In the video scene 300, a first unknown individual 304
appears walking alone at 2140 hours, a second unknown individual
306 appears walking beside the target person 302 at 2146 hours, a
third unknown individual 308 appears walking at a distance from
target person 302, and a fourth unknown individual 310 is seen
walking alone at 2153 hours. Accordingly, an attribute of each of
these four unknown individuals are determined for comparison with
other video scenes. For example, the attribute may be facial
information which may be determined from captured videos of the
each of the four unknown individuals' faces. The attribute may also
be a physical characteristic of each of the four unknown
individuals, for example height, body size, hair colour, skin
colour, and other physical features or combinations thereof. The
attribute may also be a behavioural characteristic of each of the
four unknown individuals such as, for example, the way each of the
four unknown individuals walk, stand, move, talk, other similar
characteristics or combinations thereof.
[0041] FIG. 4 illustrates a video scene analysis for more than one
location and more than one target person according to various
embodiments. Two video scenes 400 and 401 are being analysed. Video
scene 400 comprises video surveillance footage for a Location A on
2nd April, at which a first target person 402 appears at 2145
hours. Video scene 401 comprises video surveillance footage for a
Location B on 11th May, at which a second target person 404 appears
at 1125 hours. In video scene 400, an unknown individual 406
appears at 2141 hours, 4 minutes before the appearance of the
target person 402. In video scene 401, the same unknown individual
406 appears at 1128 hours, 3 minutes after the appearance of target
person 404. Accordingly, the unknown individual 406 is now
determined to appear in 2 video scenes. In an embodiment where the
predetermined threshold number is set as 1, the unknown individual
406 will be identified as a potential associate of target persons
402 and 404.
[0042] FIG. 5 shows an illustration 500 of how potential associates
are identified. Firstly, an attribute of at least one target person
is determined. For example, the attribute may be facial information
of the at least one target person which may be determined from a
picture of the at least one target person's face. The attribute may
also be a physical characteristic of the at least one target
person, for example height, body size, hair colour, skin colour,
and other physical features or combinations thereof. The attribute
may also be a behavioural characteristic of the at least one target
person such as, for example, the way the at least one target person
walks, stands, moves, talks, other similar characteristics or
combinations thereof. In the present embodiment, at 508, a group
photo or multiple photos of three target persons 502, 504 and 506
are provided. At 510, facial information of target persons 502, 504
and 506 are detected from the provided photos. The detected facial
information may then be used as the attribute. It will be
appreciated that the photographs may be physical copies or soft
copies, where the physical copies may be scanned to detect the
facial features of the target persons. Further, other mediums such
as videos can also be used for determining the attributes.
[0043] Further, a plurality of videos is provided. The plurality of
videos may be video recordings of locations captured by
surveillance cameras, hand phone cameras, CCTV (closed-circuit
television) cameras, web-cams or other similar devices. The
locations may be places where the at least one target person has
been seen, known to have been to or frequented, or suspected
locations where the at least one target person provides or receives
information to or from associates of the same criminal group. The
plurality of videos may be in a file format such as mp4, avi, mkv,
wmv, mov or other similar video format. Further, each of the
plurality of videos may indicate a time, date and location at which
each respective video is recorded. In an embodiment, the plurality
of videos may be processed into an entry database consisting of one
or more entries, wherein each of the one or more entries represents
an appearance of a person at a time, date and location in the
plurality of videos, wherein each of the one or more entries
indicates an attribute of the person.
[0044] At 512, appearances of the three target persons 502, 504 and
506 are identified from the plurality of videos. This may be
achieved by identifying, from the plurality of videos, an
individual possessing the determined attribute as the respective
target person. In the present embodiment, the attribute used for
the identification of target persons 502, 504 and 506 in the
plurality of videos is the facial information as determined in 510.
For example, an individual appearing in the plurality of videos and
having the same facial information as target person 502 will be
identified as the target person 502, an individual appearing in the
plurality of videos and having the same facial information as
target person 504 will be identified as the target person 504, and
an individual appearing in the plurality of videos and having the
same facial information as target person 506 will be identified as
the target person 506.
[0045] After identifying all video appearances of the target
persons 502, 504 and 506 in the plurality of videos, at 514, an
appearance consolidator consolidates the identified video
appearances of the three target persons 502, 504 and 506 from the
plurality of videos. For example, identified video appearances 522
is based on the identified appearances in the plurality of videos
of target person 502, identified video appearances 524 is based on
the identified appearances in the plurality of videos of target
person 504 and identified video appearances 526 is based on the
identified appearances in the plurality of videos of target person
506. The consolidation may be based on a time range, a date, a
location or a combination thereof, wherein identified appearances
of a target person that occur at a same location, date and/or time
range may be grouped together to form a logical appearance
sequence.
[0046] The identified video appearances of the target persons may
come from one or more videos of the plurality of videos. In the
present embodiment, identified video appearances 526 is based on
appearances of target person 506 in one or more videos of the
plurality of videos, wherein the one or more videos may occur at a
same time range, date, location or a combination thereof, such that
the video appearances 526 comprises one logical appearance of the
target person 506. Identified video appearances 522 is based on
appearances of target person 502 in at least two videos of the
plurality of videos, where video appearances 528 of target person
502 are identified from a first batch of one or more videos, and
video appearances 530 of target person 502 are identified from a
second batch of one or more videos. The first batch of one or more
videos may occur at a same time range, date, location or a
combination thereof, such that the video appearances 528 comprises
one logical appearance of the target person 502. Likewise, the
second batch of one or more videos may occur at a same time range,
date, location or a combination thereof, such that the video
appearances 530 comprises one logical appearance of the target
person 502. For example, the first and second batch of one or more
videos may be surveillance videos of a location recorded on a same
date, where video appearances 528 of target person 502 from the
first batch of one or more videos may be occurring at an earlier
time and video appearances 530 of target person 502 from the second
batch of one or more videos may be occurring at a later time, such
that video appearances 528 forms a first logical appearance of
target person 502, while video appearances 530 forms a second
logical appearance of target person 502. Accordingly, the
consolidated video appearances 522 comprises two logical
appearances of target person 502.
[0047] Further, identified appearances 524 is based on appearances
of target person 504 in at least two videos of the plurality of
videos, where video appearances 532 of target person 504 are
identified from a first batch of one or more videos, and video
appearances 534 of target person 504 are identified from a second
batch of one or more videos. The first batch of one or more videos
may occur at a same time range, date, location or a combination
thereof, such that the video appearances 532 comprises one logical
appearance of the target person 504. Likewise, the second batch of
one or more videos may occur at a same time range, date, location
or a combination thereof, such that the video appearances 534
comprises one logical appearance of the target person 504. For
example, the first and second batch of one or more videos may be
surveillance videos of a location recorded on a same date, where
video appearances 532 of target person 504 from the first batch of
one or more videos may be occurring at an earlier time and video
appearances 534 of target person 504 from the second batch of one
or more videos may be occurring at a later time, such that video
appearances 532 forms a first logical appearance of target person
504, while video appearances 534 from a second logical appearance
of target person 504. Accordingly, the consolidated video
appearances 524 comprises two logical appearances of target person
504. It will be appreciated that more than one consolidated video
appearances for each target person may be formed based on the
identified appearances, where each consolidated appearance may
correspond to a time range, a date, a location, or combinations
thereof in which the identified appearances occur in the plurality
of videos.
[0048] Based on the identified logical appearances that are
consolidated at 514, a plurality of video scenes is established by
the appearance consolidator. At 516, video scene 536 is established
based on, for example, the consolidated appearances 526 of target
person 506. The video scene 536 comprises a first portion 540, a
second portion 542 and a third portion 544. The first portion 540
may comprise a one or more video footages from which consolidated
video appearances 526 of target person 506 are identified. The
first portion 540 may further comprise one or more video footages
in which appearances of the target person 506 are not found, but
these one or more video footages are of a time, a date, a location,
or combinations thereof that matches the time, the date, the
location, or combinations thereof of the one or more video footages
from which the consolidated video appearances 526 of target person
506 are identified. Advantageously, this will take into
consideration all available surveillance footage of a location, so
as to cover scenarios in which the target person is at a spot where
only one of the surveillance cameras can capture the person on
video.
[0049] In addition to the first portion 540 of the video scene 536,
the second portion 542 extends the duration of the video scene 536
by a first predetermined duration, such that the video scene 536
begins at the first predetermined duration before a first
appearance of the target person 506 as identified in the first
portion 540 of the video scene 536. Accordingly, the second portion
542 may comprise one or more video footages of a time, a date, a
location, or combinations thereof that matches the time, the date,
the location, or combinations thereof of the one or more video
footages of the first portion 540 of video scene 536, wherein the
one or more video footages of the second portion 542 begins at the
first predetermined duration before the first appearance of the
target person 506 as identified in the first portion 540 of the
video scene 536. Advantageously, the inclusion of the second
portion 542 of the video scene 536 allows identification of
potential associates of the target person 506 even if they are not
co-appearing together with the target person 506 in the videos, but
only appearing before the target person 506 arrives at the recorded
location, possibly just to leave an object for retrieval by the
target person 506.
[0050] Further, there is the third portion 544 of the video scene
536 that extends the duration of the video scene 536 by a second
predetermined duration, such that the video scene 536 ends at the
second predetermined duration after a last appearance of the target
person 506 as identified in the first portion 540 of the video
scene 536. Accordingly, the third portion 544 may comprise one or
more video footages of a time, a date, a location, or combinations
thereof that matches the time, the date, the location, or
combinations thereof of the one or more video footages of the first
portion 540 of video scene 536, wherein the one or more video
footages of the third portion 544 ends at the second predetermined
duration after the last appearance of the target person 506 as
identified in the first portion 540 of the video scene 536.
Advantageously, the inclusion of the third portion 544 of the video
scene 536 allows identification of potential associates of the
target person 506 even if they are not co-appearing together with
the target person 506 in the videos, but only appearing after the
target person 506 leaves the recorded location, possibly to
retrieve an object that was intentionally left behind by the target
person 506.
[0051] Similar to video scene 536, video scene 538 is established
based on, for example, video appearances 532 in the consolidated
appearances 524 of target person 504. The video scene 538 comprises
a first portion 546, a second portion 548 and a third portion 550.
The first portion 546 may comprise one or more video footages from
which video appearances 532 of target person 504 are identified.
The first portion 546 may further comprise one or more video
footages in which appearances of the target person 504 are not
found, but these one or more video footages are of a time, a date,
a location, or combinations thereof that matches the time, the
date, the location, or combinations thereof of the one or more
video footages from which the consolidated video appearances 532 of
target person 504 are identified. Advantageously, this will take
into consideration all available surveillance footage of a
location, so as to cover scenarios in which the target person is at
a spot where only one of the surveillance cameras can capture the
person on video.
[0052] In addition to the first portion 546 of the video scene 538,
the second portion 548 extends the duration of the video scene 538
by a first predetermined duration, such that the video scene 538
begins at the first predetermined duration before a first
appearance of the target person 504 as identified in the first
portion 546 of the video scene 538. Accordingly, the second portion
548 may comprise one or more video footages of a time, a date, a
location, or combinations thereof that matches the time, the date,
the location, or combinations thereof of the one or more video
footages of the first portion 546 of video scene 538, wherein the
one or more video footages of the second portion 548 begins at the
first predetermined duration before the first appearance of the
target person 504 as identified in the first portion 546 of the
video scene 538. Advantageously, the inclusion of the second
portion 548 of the video scene 538 allows identification of
potential associates of the target person 504 even if they are not
co-appearing together with the target person 504 in the videos, but
only appearing before the target person 504 arrives at the recorded
location, possibly just to leave an object for retrieval by the
target person 504.
[0053] Further, there is the third portion 550 of the video scene
538 that extends the duration of the video scene 538 by a second
predetermined duration, such that the video scene 538 ends at the
second predetermined duration after a last appearance of the target
person 504 as identified in the first portion 546 of the video
scene 538. Accordingly, the third portion 550 may comprise one or
more video footages of a time, a date, a location, or combinations
thereof that matches the time, the date, the location, or
combinations thereof of the one or more video footages of the first
portion 546 of video scene 538, wherein the one or more video
footages of the third portion 550 ends at the second predetermined
duration after the last appearance of the target person 504 as
identified in the first portion 546 of the video scene 538.
Advantageously, the inclusion of the third portion 550 of the video
scene 538 allows identification of potential associates of the
target person 504 even if they are not co-appearing together with
the target person 504 in the videos, but only appearing after the
target person 504 leaves the recorded location, possibly to
retrieve an object that was intentionally left behind by the target
person 504.
[0054] After establishment of the video scenes 536 and 538, a
co-appearance search module determines every individual besides the
target persons 502, 504 and 506 who appear in the video scenes. The
determination process may comprise determining an attribute of each
of the one or more individuals who appear in any of the video
scenes 536 and 538. The attribute may be, for example, facial
information, physical characteristics, behaviour characteristics,
other similar characteristics or combinations thereof that may be
used to identify each of the one or more individuals. The
determination process may further comprise determining a time, a
date, a location, a target person who appeared in the same video
scene as the respective individual, or combinations thereof for
each of the one or more individuals who appear in any of the video
scenes 536 and 538. The determination process includes all three
portions 540, 542 and 544 of video scene 536, as well as all three
portions 546, 548 and 550 of video scene 538. Advantageously,
individuals who appear within the first predetermined duration
before the first appearance of the respective target person in the
respective video scene, and individuals who appear within the
second predetermined duration after the last appearance of the
respective target person in the respective video scene are
considered in the determination process. It will be understood that
video scenes will similarly be established for each of the
remaining video appearances 528, 530 and 534, where these video
scenes will also be considered in the determination process.
[0055] After determining each of the one or more individuals
appearing in the video scenes 536 and 538, an appearance analyser
determines the individuals who appear in more than a predetermined
threshold number of the video scenes. Referring to 518, three
persons A, B and C are found to have appeared in any of the video
scene 536 and/or video scene 538. In the present embodiment, the
determination process comprises determining an attribute and a
location for each of the one or more individuals who appear in any
of the video scenes 536 and 538, where video scene 536 comprises
one or more camera surveillance footage of a first location and
video scene 538 comprises one or more camera surveillance footage
of a second location. Based on the results of the co-appearance
search module at 516, Person A is found to have appeared in the
video scene 536. Accordingly, as shown in 552, Person A has one
appearance in one location. Person B is found to have appeared in
the video scene 538. Accordingly, as shown in 554, Person B also
has one appearance in one location. Person C, however, is found to
have appeared in both video scenes 536 and 538. Accordingly, as
shown in 556, Person C has two appearances in two locations.
[0056] In the present embodiment, the predetermined threshold
number is set as 1. Therefore, if an individual is determined to
have appeared in 2 or more video scenes, the individual is then
determined to be a potential associate of the target persons. In
this case, since Person C is found to have appeared in two video
scenes, namely video scene 536 and video scene 538, Person C will
be output at 520 as the potential associate of target persons 506
and 508. It will be understood that the predetermined threshold
number may be set according to any other number that may produce an
optimal result, and may vary according to the number of video
scenes being considered.
[0057] FIG. 6 depicts an exemplary computing device 600,
hereinafter interchangeably referred to as a computer system 600 or
as a device 600, where one or more such computing devices 600 may
be used to implement the identification device 200 shown in FIG. 2.
The following description of the computing device 600 is provided
by way of example only and is not intended to be limiting.
[0058] As shown in FIG. 6, the example computing device 600
includes a processor 604 for executing software routines. Although
a single processor is shown for the sake of clarity, the computing
device 600 may also include a multi-processor system. The processor
604 is connected to a communication infrastructure 606 for
communication with other components of the computing device 600.
The communication infrastructure 606 may include, for example, a
communications bus, cross-bar, or network.
[0059] The computing device 600 further includes a primary memory
608, such as a random access memory (RAM), and a secondary memory
610. The secondary memory 610 may include, for example, a storage
drive 612, which may be a hard disk drive, a solid state drive or a
hybrid drive and/or a removable storage drive 614, which may
include a magnetic tape drive, an optical disk drive, a solid state
storage drive (such as a USB flash drive, a flash memory device, a
solid state drive or a memory card), or the like. The removable
storage drive 614 reads from and/or writes to a removable storage
medium 644 in a well-known manner. The removable storage medium 644
may include magnetic tape, optical disk, non-volatile memory
storage medium, or the like, which is read by and written to by
removable storage drive 614. As will be appreciated by persons
skilled in the relevant art(s), the removable storage medium 644
includes a computer readable storage medium having stored therein
computer executable program code instructions and/or data.
[0060] In an alternative implementation, the secondary memory 610
may additionally or alternatively include other similar means for
allowing computer programs or other instructions to be loaded into
the computing device 600. Such means can include, for example, a
removable storage unit 622 and an interface 640. Examples of a
removable storage unit 622 and interface 640 include a program
cartridge and cartridge interface (such as that found in video game
console devices), a removable memory chip (such as an EPROM or
PROM) and associated socket, a removable solid state storage drive
(such as a USB flash drive, a flash memory device, a solid state
drive or a memory card), and other removable storage units 622 and
interfaces 640 which allow software and data to be transferred from
the removable storage unit 622 to the computer system 600.
[0061] The computing device 600 also includes at least one
communication interface 624. The communication interface 624 allows
software and data to be transferred between computing device 600
and external devices via a communication path 626. In various
embodiments of the inventions, the communication interface 624
permits data to be transferred between the computing device 600 and
a data communication network, such as a public data or private data
communication network. The communication interface 624 may be used
to exchange data between different computing devices 600 which such
computing devices 600 form part an interconnected computer network.
Examples of a communication interface 624 can include a modem, a
network interface (such as an Ethernet card), a communication port
(such as a serial, parallel, printer, GPIB, IEEE 1394, RJ45, USB),
an antenna with associated circuitry and the like. The
communication interface 624 may be wired or may be wireless.
Software and data transferred via the communication interface 624
are in the form of signals which can be electronic,
electromagnetic, optical or other signals capable of being received
by communication interface 624. These signals are provided to the
communication interface via the communication path 626.
[0062] As shown in FIG. 6, the computing device 600 further
includes a display interface 602 which performs operations for
rendering images to an associated display 630 and an audio
interface 632 for performing operations for playing audio content
via associated speaker(s) 634.
[0063] As used herein, the term "computer program product" (or
computer readable medium, which may be a non-transitory computer
readable medium) may refer, in part, to removable storage medium
644, removable storage unit 622, a hard disk installed in storage
drive 612, or a carrier wave carrying software over communication
path 626 (wireless link or cable) to communication interface 624.
Computer readable storage media (or computer readable media) refers
to any non-transitory, non-volatile tangible storage medium that
provides recorded instructions and/or data to the computing device
600 for execution and/or processing. Examples of such storage media
include magnetic tape, CD-ROM, DVD, Blu-ray.TM. Disc, a hard disk
drive, a ROM or integrated circuit, a solid state storage drive
(such as a USB flash drive, a flash memory device, a solid state
drive or a memory card), a hybrid drive, a magneto-optical disk, or
a computer readable card such as a PCMCIA card and the like,
whether or not such devices are internal or external of the
computing device 600. Examples of transitory or non-tangible
computer readable transmission media that may also participate in
the provision of software, application programs, instructions
and/or data to the computing device 600 include radio or infra-red
transmission channels as well as a network connection to another
computer or networked device, and the Internet or Intranets
including e-mail transmissions and information recorded on Websites
and the like.
[0064] The computer programs (also called computer program code)
are stored in primary memory 608 and/or secondary memory 610.
Computer programs can also be received via the communication
interface 624. Such computer programs, when executed, enable the
computing device 600 to perform one or more features of embodiments
discussed herein. In various embodiments, the computer programs,
when executed, enable the processor 604 to perform features of the
above-described embodiments. Accordingly, such computer programs
represent controllers of the computer system 600.
[0065] Software may be stored in a computer program product and
loaded into the computing device 600 using the removable storage
drive 614, the storage drive 612, or the interface 640. The
computer program product may be a non-transitory computer readable
medium. Alternatively, the computer program product may be
downloaded to the computer system 600 over the communications path
626. The software, when executed by the processor 604, causes the
computing device 600 to perform functions of embodiments described
herein.
[0066] It is to be understood that the embodiment of FIG. 6 is
presented merely by way of example. Therefore, in some embodiments
one or more features of the computing device 600 may be omitted.
Also, in some embodiments, one or more features of the computing
device 600 may be combined together. Additionally, in some
embodiments, one or more features of the computing device 600 may
be split into one or more component parts. The primary memory 608
and/or the secondary memory 610 may serve(s) as the memory for the
device 200; while the processor 604 may serve as the processor of
the identification device 200.
[0067] Some portions of the description herein are explicitly or
implicitly presented in terms of algorithms and functional or
symbolic representations of operations on data within a computer
memory. These algorithmic descriptions and functional or symbolic
representations are the means used by those skilled in the data
processing arts to convey most effectively the substance of their
work to others skilled in the art. An algorithm is here, and
generally, conceived to be a self-consistent sequence of steps
leading to a desired result. The steps are those requiring physical
manipulations of physical quantities, such as electrical, magnetic
or optical signals capable of being stored, transferred, combined,
compared, and otherwise manipulated.
[0068] Unless specifically stated otherwise, and as apparent from
the description herein, it will be appreciated that throughout the
present specification, discussions utilizing terms such as
"receiving", "providing", "identifying", "scanning", "determining",
"generating", "outputting", or the like, refer to the action and
processes of a computer system, or similar electronic device, that
manipulates and transforms data represented as physical quantities
within the computer system into other data similarly represented as
physical quantities within the computer system or other information
storage, transmission or display devices.
[0069] The present specification also discloses apparatus for
performing the operations of the methods. Such apparatus may be
specially constructed for the required purposes, or may comprise a
computer or other device selectively activated or reconfigured by a
computer program stored in the computer. The algorithms and
displays presented herein are not inherently related to any
particular computer or other apparatus. Various machines may be
used with programs in accordance with the teachings herein.
Alternatively, the construction of more specialized apparatus to
perform the required method steps may be appropriate. The structure
of a computer suitable for executing the various methods/processes
described herein will appear from the description herein.
[0070] In addition, the present specification also implicitly
discloses a computer program, in that it would be apparent to the
person skilled in the art that the individual steps of the method
described herein may be put into effect by computer code. The
computer program is not intended to be limited to any particular
programming language and implementation thereof. It will be
appreciated that a variety of programming languages and coding
thereof may be used to implement the teachings of the disclosure
contained herein. Moreover, the computer program is not intended to
be limited to any particular control flow. There are many other
variants of the computer program, which can use different control
flows without departing from the spirit or scope of the
invention.
[0071] Furthermore, one or more of the steps of the computer
program may be performed in parallel rather than sequentially. Such
a computer program may be stored on any computer readable medium.
The computer readable medium may include storage devices such as
magnetic or optical disks, memory chips, or other storage devices
suitable for interfacing with a computer. The computer readable
medium may also include a hard-wired medium such as exemplified in
the Internet system, or wireless medium such as exemplified in the
GSM mobile telephone system. The computer program when loaded and
executed on such a computer effectively results in an apparatus
that implements the steps of the preferred method.
[0072] According to various embodiments, a "module" may be
understood as any kind of a logic implementing entity, which may be
special purpose circuitry or a processor executing software stored
in a memory, firmware, or any combination thereof. Thus, in an
embodiment, a "module" may be a hard-wired logic circuit or a
programmable logic circuit such as a programmable processor, e.g. a
microprocessor (e.g. a Complex Instruction Set Computer (CISC)
processor or a Reduced Instruction Set Computer (RISC) processor).
A "module" may also be a processor executing software, e.g. any
kind of computer program, e.g. a computer program using a virtual
machine code such as e.g. Java. Any other kind of implementation of
the respective functions which will be described in more detail
below may also be understood as a "module" in accordance with an
alternative embodiment.
[0073] It will be appreciated by a person skilled in the art that
numerous variations and/or modifications may be made to the present
invention as shown in the specific embodiments without departing
from the spirit or scope of the invention as broadly described. The
present embodiments are, therefore, to be considered in all
respects to be illustrative and not restrictive.
[0074] For example, the whole or part of the exemplary embodiments
disclosed above can be described as, but not limited to, the
following supplementary notes.
[0075] (Supplementary Note 1)
[0076] A method for identifying potential associates of at least
one target person, the method comprising:
[0077] providing a plurality of videos;
[0078] identifying appearances of the at least one target person in
the plurality of videos;
[0079] establishing a plurality of video scenes from the plurality
of videos, wherein each one of the plurality of video scenes begins
at a first predetermined duration before a first appearance of the
at least one target person in the respective video scene and ends
at a second predetermined duration after a last appearance of said
at least one target person in the respective video scene;
[0080] determining individuals who appear in more than a
predetermined threshold number of the plurality of video scenes;
and
[0081] identifying the individuals as potential associates of the
at least one target person.
[0082] (Supplementary Note 2)
[0083] The method according to note 1, wherein identifying the
appearances of a respective target person of the at least one
target person from the plurality of videos further comprises:
determining an attribute of the respective target person; and
identifying, from the plurality of videos, an individual possessing
the attribute as the respective target person.
[0084] (Supplementary Note 3)
[0085] The method according to note 2, wherein the attribute
further comprises facial information of the respective target
person.
[0086] (Supplementary Note 4)
[0087] The method according to note 2, wherein the attribute
further comprises a physical characteristic of the respective
target person.
[0088] (Supplementary Note 5)
[0089] The method according to note 2, wherein the attribute
further comprises a behavioural characteristic of the respective
target person.
[0090] (Supplementary Note 6)
[0091] The method according to note 1, wherein any one of the
plurality of video scenes further comprises one or more camera
surveillance footage of a location.
[0092] (Supplementary Note 7)
[0093] The method according to note 6, wherein each of the one or
more camera surveillance footage shows a different view of the
location.
[0094] (Supplementary Note 8)
[0095] An identification device configured to identify potential
associates of at least one target person, the identification device
comprising:
[0096] a receiving module configured to receive a plurality of
videos;
an appearance search module configured to identify appearances of
the at least one target person in the plurality of videos;
[0097] an appearance consolidator module configured to establish a
plurality of video scenes from the plurality of videos, wherein
each one of the plurality of video scenes begins at a first
predetermined duration before a first appearance of the at least
one target person in the respective video scene and ends at a
second predetermined duration after a last appearance of said at
least one target person in the respective video scene;
[0098] a co-appearance search module configured to search for
individuals who appear in the plurality of video scenes;
[0099] an appearance analyzer module configured to determine which
of the individuals appear in more than a predetermined threshold
number of the plurality of video scenes; and
[0100] an output module configured to identify the individuals who
appear in more than a predetermined threshold number of the
plurality of video scenes as the potential associates of the at
least one target person.
[0101] (Supplementary Note 9)
[0102] The identification device according to note 8, wherein the
appearance search module is further configured to:
[0103] determine an attribute of a respective target person of the
at least one target person; and
[0104] identify, from the plurality of videos, an individual
possessing the attribute as the respective target person.
[0105] (Supplementary Note 10)
[0106] The identification device according to note 9, wherein the
attribute further comprises facial information of the respective
target person.
[0107] (Supplementary Note 11)
[0108] The identification device according to note 9, wherein the
attribute further comprises a physical characteristic of the
respective target person.
[0109] (Supplementary Note 12)
[0110] The identification device according to note 9, wherein the
attribute further comprises a behavioural characteristic of the
respective target person.
[0111] (Supplementary Note 13)
[0112] The identification device according to note 8, wherein any
one of the plurality of video scenes further comprises one or more
camera surveillance footage of a location.
[0113] (Supplementary Note 14)
[0114] The identification device according to note 13, wherein each
of the one or more camera surveillance footage shows a different
view of the location.
[0115] (Supplementary Note 15)
[0116] A non-transitory computer readable medium having stored
thereon instructions which, when executed by a processor, make the
processor carry out a method for identifying potential associates
of at least one target person, the method comprising:
[0117] receiving a plurality of videos;
[0118] identifying appearances of the at least one target person in
the plurality of videos;
establishing a plurality of video scenes from the plurality of
videos, wherein each one of the plurality of video scenes begins at
a first predetermined duration before a first appearance of the at
least one target person in the respective video scene and ends at a
second predetermined duration after a last appearance of said at
least one target person in the respective video scene;
[0119] determining individuals who appear in more than a threshold
number of the plurality of video scenes; and
[0120] identifying the individuals as potential associates of the
at least one target person.
[0121] This application is based upon and claims the benefit of
priority from Singapore Patent Application No. 10201807678 W, filed
on Sep. 6, 2018, the disclosure of which is incorporated herein in
its entirety by reference.
REFERENCE SIGNS LIST
[0122] 202 Receiving Module [0123] 204 Appearance Search Module
[0124] 206 Consolidator Module [0125] 208 Co-appearance Search
Module [0126] 210 Analyser Module [0127] 212 Output Module [0128]
302 Target Person [0129] 304 First Unknown Individual [0130] 306
Second Unknown Individual [0131] 308 Third Unknown Individual
[0132] 402 First Target Person [0133] 404 Second Target Person
[0134] 406 Unknown Individual
* * * * *