Patents by Inventor Lon William Risinger
Lon William Risinger has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Patent number: 8620028Abstract: 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 an object's motion frame-to-frame. Classes of the objects are determined and semantic representations of the objects are generated. The semantic representations are used to determine objects' behaviors and to learn about behaviors occurring in an environment depicted by the acquired video streams. This way, the system learns rapidly and in real-time normal and abnormal behaviors for any environment by analyzing movements or activities or absence of such in the environment and identifies and predicts abnormal and suspicious behavior based on what has been learned.Type: GrantFiled: March 6, 2012Date of Patent: December 31, 2013Assignee: Behavioral Recognition Systems, Inc.Inventors: 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
-
Publication number: 20120163670Abstract: 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 an object's motion frame-to-frame. Classes of the objects are determined and semantic representations of the objects are generated. The semantic representations are used to determine objects' behaviors and to learn about behaviors occurring in an environment depicted by the acquired video streams. This way, the system learns rapidly and in real-time normal and abnormal behaviors for any environment by analyzing movements or activities or absence of such in the environment and identifies and predicts abnormal and suspicious behavior based on what has been learned.Type: ApplicationFiled: March 6, 2012Publication date: June 28, 2012Applicant: BEHAVIORAL RECOGNITION SYSTEMS, INC.Inventors: 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
-
Patent number: 8131012Abstract: 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 an object's motion frame-to-frame. Classes of the objects are determined and semantic representations of the objects are generated. The semantic representations are used to determine objects' behaviors and to learn about behaviors occurring in an environment depicted by the acquired video streams. This way, the system learns rapidly and in real-time normal and abnormal behaviors for any environment by analyzing movements or activities or absence of such in the environment and identifies and predicts abnormal and suspicious behavior based on what has been learned.Type: GrantFiled: February 8, 2008Date of Patent: March 6, 2012Assignee: BEHAVIORAL RECOGNITION SYSTEMS, Inc.Inventors: 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
-
Publication number: 20110043689Abstract: Techniques are disclosed for detecting a field-of-view change for a video feed. These techniques differentiate between a new or changed scene and a temporary variation in the scene to accurately detect field-of-view changes for the video feed. A field-of-view change is detected when the position of a camera providing the video feed changes, the video feed is switched to a different camera, the video feed is disconnected, or the camera providing the video feed is obscured. A false-positive field-of-view change is not detected when the scene changes due to a sudden variation in illumination, obstruction of a portion of the camera providing the video feed, blurred images due to an out-of-focus camera, or a transition between bright and dark light when the video feed transitions between color and near infrared capture modes.Type: ApplicationFiled: August 18, 2009Publication date: February 24, 2011Inventors: Wesley Kenneth Cobb, Dennis Gene Urech, Bobby Ernest Blythe, Rajkiran Kumar Gottumukkal, Kishor Adinath Saitwal, Tao Yang, Lon William Risinger
-
Publication number: 20110044536Abstract: Techniques are disclosed for extracting micro-features at a pixel-level based on characteristics of one or more images. Importantly, the extraction is unsupervised, i.e., performed independent of any training data that defines particular objects, allowing a behavior-recognition system to forgo a training phase and for object classification to proceed without being constrained by specific object definitions. A micro-feature extractor that does not require training data is adaptive and self-trains while performing the extraction. The extracted micro-features are represented as a micro-feature vector that may be input to a micro-classifier which groups objects into object type clusters based on the micro-feature vectors.Type: ApplicationFiled: August 18, 2009Publication date: February 24, 2011Inventors: Wesley Kenneth Cobb, Rajkiran Kumar Gottumukkal, Kishor Adinath Saitwal, Min-Jung Seow, Gang Xu, Lon William Risinger, Jeff Graham
-
Publication number: 20080193010Abstract: 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 an object's motion frame-to-frame. Classes of the objects are determined and semantic representations of the objects are generated. The semantic representations are used to determine objects' behaviors and to learn about behaviors occurring in an environment depicted by the acquired video streams. This way, the system learns rapidly and in real-time normal and abnormal behaviors for any environment by analyzing movements or activities or absence of such in the environment and identifies and predicts abnormal and suspicious behavior based on what has been learned.Type: ApplicationFiled: February 8, 2008Publication date: August 14, 2008Inventors: 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