1
John Eric Eaton, Wesley Kenneth Cobb, Dennis Gene Urech, Bobby Ernest Blythe, David Samuel Friedlander, Rajkiran Kumar Gottumukkal, Lon William Risinger, Kishor Adinath Saitwal, Ming Jung Seow, David Marvin Solum, Gang Xu, Tao Yang: Behavioral recognition system. BEHAVIORAL RECOGNITION SYSTEMS, Patterson & Sheridan, March 6, 2012: US08131012 (20 worldwide citation)

Embodiments of the present invention provide a method and a system for analyzing and learning behavior based on an acquired stream of video frames. Objects depicted in the stream are determined based on an analysis of the video frames. Each object may have a corresponding search model used to track ...


2
John Eric Eaton, Wesley Kenneth Cobb, Bobby Ernest Blythe, Rajkiran Kumar Gottumukkal, Kishor Adinath Saitwal: Context processor for video analysis system. Behavioral Recognition Systems, Patterson & Sheridan, June 12, 2012: US08200011 (6 worldwide citation)

Embodiments of the present invention provide a method and a system for mapping a scene depicted in an acquired stream of video frames that may be used by a machine-learning behavior-recognition system. A background image of the scene is segmented into plurality of regions representing various object ...


3
John Eric Eaton, Wesley Kenneth Cobb, Dennis Gene Urech, Bobby Ernest Blythe, David Samuel Friedlander, Rajkiran Kumar Gottumukkal, Lon William Risinger, Kishor Adinath Saitwal, Ming Jung Seow, David Marvin Solum, Gang Xu, Tao Yang: Behavioral recognition system. Behavioral Recognition Systems, Patterson & Sheridan, December 31, 2013: US08620028 (5 worldwide citation)

Embodiments of the present invention provide a method and a system for analyzing and learning behavior based on an acquired stream of video frames. Objects depicted in the stream are determined based on an analysis of the video frames. Each object may have a corresponding search model used to track ...


4
Wesley Kenneth Cobb, David Friedlander, Rajkiran Kumar Gottumukkal, Ming Jung Seow, Gang Xu: Identifying anomalous object types during classification. Behavioral Recognition Systems, Patterson & Sheridan, September 18, 2012: US08270733 (5 worldwide citation)

Techniques are disclosed for identifying anomaly object types during classification of foreground objects extracted from image data. A self-organizing map and adaptive resonance theory (SOM-ART) network is used to discover object type clusters and classify objects depicted in the image data based on ...


5
Wesley Kenneth Cobb, Bobby Ernest Blythe, David Samuel Friedlander, Rajkiran Kumar Gottumukkal, Ming Jung Seow, Gang Xu: Visualizing and updating learned trajectories in video surveillance systems. Behavioral Recognition Systems, Patterson & Sheridan, October 2, 2012: US08280153 (3 worldwide citation)

Techniques are disclosed for visually conveying a trajectory map. The trajectory map provides users with a visualization of data observed by a machine-learning engine of a behavior recognition system. Further, the visualization may provide an interface used to guide system behavior. For example, the ...


6
Wesley Kenneth Cobb, Bobby Ernest Blythe, David Samuel Friedlander, Rajkiran Kumar Gottumukkal, Kishor Adinath Saitwal: Visualizing and updating sequences and segments in a video surveillance system. Behavioral Recognition Systems, Patterson & Sheridan, July 23, 2013: US08493409 (2 worldwide citation)

Techniques are disclosed for visually conveying a sequence storing an ordered string of symbols generated from kinematic data derived from analyzing an input stream of video frames depicting one or more foreground objects. The sequence may represent information learned by a video surveillance system ...


7
John Eric Eaton, Wesley Kenneth Cobb, Bobby Ernest Blythe, Rajkiran Kumar Gottumukkal, Kishor Adinath Saitwal: Context processor for video analysis system. Behavioral Recognition Systems, Patterson & Sheridan, April 22, 2014: US08705861 (1 worldwide citation)

Embodiments of the present invention provide a method and a system for mapping a scene depicted in an acquired stream of video frames that may be used by a machine-learning behavior-recognition system. A background image of the scene is segmented into plurality of regions representing various object ...


8
Wesley Kenneth Cobb, Bobby Ernest Blythe, Rajkiran Kumar Gottumukkal, Kishor Adinath Saitwal, Gang Xu, Tao Yang: Scene preset identification using quadtree decomposition analysis. Omni AI, N W Poulsen, October 31, 2017: US09805271

Techniques are disclosed for matching a current background scene of an image received by a surveillance system with a gallery of scene presets that each represent a previously captured background scene. A quadtree decomposition analysis is used to improve the robustness of the matching operation whe ...


9
Wesley Kenneth Cobb, Bobby Ernest Blythe, Rajkiran Kumar Gottumukkal, Ming Jung Seow: Visualizing and updating learned event maps in surveillance systems. Behavioral Recognition Systems, Patterson & Sheridan, January 7, 2014: US08625884

Techniques are disclosed for visually conveying an event map. The event map may represent information learned by a surveillance system. A request may be received to view the event map for a specified scene. The event map may be generated, including a background model of the specified scene and at le ...


10
Wesley Kenneth Cobb, David Friedlander, Rajkiran Kumar Gottumukkal, Ming Jung Seow, Gang Xu: Identifying anomalous object types during classification. Behavioral Recognition Systems, Patterson & Sheridan, October 1, 2013: US08548198

Techniques are disclosed for identifying anomaly object types during classification of foreground objects extracted from image data. A self-organizing map and adaptive resonance theory (SOM-ART) network is used to discover object type clusters and classify objects depicted in the image data based on ...