Method for finding paths in video

• US 8,823,804 B2
• Filed: 01/19/2012
• Issued: 09/02/2014
• Est. Priority Date: 09/24/2004
• Status: Active Grant

• Current Assignee: Motorola Solutions, Inc.
• Original Assignee: ObjectVideo Incorporated (Alarm.com Holdings, Inc.)
• Inventors: Haering, Niels, Rasheed, Zeeshan, Yu, Li, Chosak, Andrew J.
• Primary Examiner(s): Gilles, Jude Jean
• Assistant Examiner(s): Means, Jaren M
• Application Number:
  US13/354,141
• Publication Number:
  US 20120268594A1
• Time in Patent Office: 957 Days
• Field of Search: 348/143, 348/152, 348/169
• US Class Current: 348/169
• CPC Class Codes: G01S 3/7864 T.V. type tracking systems
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/20101 Interactive definition of point of interest, landmark or seed
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 2207/30241 Trajectory
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/74 involving reference images or patches
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G08B 13/19613 Recognition of a predetermined image pattern or behaviour pattern indicating theft or intrusion
• CPC Class Codes: G08B 31/00 Predictive alarm systems characterised by extrapolation or other computation using updated historic data
• CPC Class Codes: H04N 7/181 for receiving images from a plurality of remote sources
• CPC Class Codes: H04N 7/183 for receiving images from a single remote source

Abstract

A system for detecting behavior of a target may include: a target detection engine, adapted to detect at least one target from one or more objects from a video surveillance system recording a scene; a path builder, adapted to create at least one mature path model from analysis of the behavior of a plurality of targets in the scene, wherein the at least one mature path model includes a model of expected target behavior with respect to the at least one path model; and a target behavior analyzer, adapted to analyze and identify target behavior with respect to the at least one mature path model. The system may further include an alert generator, adapted to generate an alert based on the identified behavior.

Claims

1. A video processing system comprising:

an up-stream video processing device to accept an input video sequence and to output target information derived from at least one target in said input video sequence, wherein said target information comprises at least one target property or at least one function of said at least one target property;

a target property map builder, coupled to said up-stream video processing device to receive at least a portion of said target information and to build at least one target property map for at least one target type, wherein said target property map comprises a statistical model based on a record of said at least one target property from instances of at least one target type or said at least one function of said at least one target property from instances of said at least one target type in said input video sequence, wherein the statistical model corresponding to an image location, target property or function of target properties and target type is a record of said property of instances of targets of said type that pass through said location, and wherein the statistical model represents at least one of a normal behavior or a normal property of instances of targets of said type that pass through said location; and

the target property map builder being further configured to, for a given target;

consider at least one instance of the target;

determine if said at least one instance of the target is a bad instance, and

if said at least one instance of the target is a bad instance, filter said at least one instance of the target by ignoring said at least one instance of the target.

2. The system according to claim 1, wherein said up-stream video processing device comprises:

a detection device to receive said input video sequence;

a tracking device coupled to said detection device; and

a classification device coupled to said tracking device, an output of said classification device being provided to said target property map builder.

3. The system according to claim 1, further comprising:

an event detection device coupled to receive an output of said target property map builder and to output one or more detected events that do not conform to the at least one of the normal behavior or the normal property based on the statistical model.

4. The system according to claim 3, further comprising:

an event specification interface coupled to said event detection device to provide one or more events of interest to said event detection device.

5. The system according to claim 4, wherein said event specification interface comprises a graphical user interface.

6. The system according to claim 1, wherein said target property map builder provides feedback to said up-stream video processing device.

7. The system according to claim 1, wherein said target property map builder comprises:

at least one buffer.

8. The system according to claim 1, wherein said at least one location comprises at least one scene-based location.

9. The system according to claim 1, wherein said at least one location comprises at least one image-based location.

10. The system according to claim 1, wherein said video processing system is replaced with a sensor processing system.

11. A method of video processing, comprising:

processing an input video sequence to obtain target information derived from at least one target in said input video sequence, wherein said target information comprises at least one target property or at least one function of said at least one target property;

building at least one target property map that comprises a statistical model based on a record of said at least one target property or said at least one function of said at least one target property from said at least one target in said input video sequence, wherein the statistical model corresponding to an image location, target property or function of target properties and target type is a record of said property of instances of targets of said type that pass through said location, and wherein the statistical model represents at least one of a normal behavior or a normal property of instances of targets of said type that pass through said location; and

wherein said building at least one target property map further includes,

considering at least one instance of the target;

determining if said at least one instance of the target is a bad instance, and

if said at least one instance of the target is a bad instance, filtering said at least one instance of the target by ignoring said at least one instance of the target.

12. The method according to claim 11, wherein said processing an input video sequence comprises:

detecting at least one target;

tracking at least one target; and

classifying at least one target.

13. The method according to claim 11, wherein said building at least one target property map further comprises:

if at least one instance of the target is mature, updating at least one map model corresponding to at least one location where an instance of the target is mature.

14. The method according to claim 13, wherein said building at least one target property map further comprises:

determining if at least one model forming part of said at least one target property map is mature.

15. The method according to claim 11, further comprising:

detecting at least one event based on said at least one target property map.

16. The method according to claim 15, wherein said detecting at least one event comprises:

for a given target, comparing at least one corresponding property model of the target with at least one property of said at least one target property map, at the corresponding location.

17. The method according to claim 16, wherein said comparing comprises:

using a user-defined comparison criterion.

18. The method according to claim 15, further comprising:

obtaining at least one user-defined criterion for event detection.

22. The method according to claim 11, wherein said at least one location comprises at least one scene-based location.

23. The method according to claim 11, wherein said at least one location comprises at least one image-based location.

19. A non-transitory computer-readable medium containing instructions that, when executed by a processor, cause the processor to:

process an input video sequence to obtain target information derived from at least one target in said input video sequence, wherein said target information comprises at least one target property or at least one function of said at least one target property; and

build at least one target property map that comprises a statistical model based on a record of said at least one target property or said at least one function of said at least one target property from said at least one target in said input video sequence, wherein the statistical model corresponding to an image location, target property or function of target properties and target type is a record of said property of instances of targets of said type that pass through said location, and wherein the statistical model represents at least one of a normal behavior or a normal property of instances of targets of said type that pass through said location; and

wherein said building at least one target property map further includes,

considering at least one instance of the target;

determining if said at least one instance of the target is a bad instance, and

if said at least one instance of the target is a bad instance, filtering said at least one instance of the target by ignoring said at least one instance of the target.

20. A video processing system comprising:

a computer system; and

the computer-readable medium according to claim 19.

21. A video surveillance system comprising:

at least one camera to generate an input video sequence; and

the video processing system according to claim 20.