Patents Assigned to Recognition Systems, Inc.
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Patent number: 9934786Abstract: A system is disclosed for facilitating free form dictation, including directed dictation and constrained recognition and/or structured transcription among users having heterogeneous native (legacy) protocols for generating, transcribing, and exchanging recognized and transcribed speech. The system includes at least one system transaction manager having a “system protocol,” to receive a verified, streamed speech information request from at least one authorized user employing a first legacy user protocol. The speech information request which includes spoken text and system commands is generated using a user interface capable of bi-directional communication with the system transaction manager and supporting dictation applications, including prompts to direct user dictation in response to user system protocol commands and systems transaction manager commands.Type: GrantFiled: January 6, 2017Date of Patent: April 3, 2018Assignee: Advanced Voice Recognition Systems, Inc.Inventors: Joseph H. Miglietta, Michael K. Davis
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Patent number: 9507768Abstract: Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.Type: GrantFiled: August 11, 2014Date of Patent: November 29, 2016Assignee: Behavioral Recognition Systems, Inc.Inventors: Wesley Kenneth Cobb, Ming-Jung Seow, Curtis Edward Cole, Jr., Cody Shay Falcon, Benjamin A. Konosky, Charles Richard Morgan, Aaron Poffenberger, Thong Toan Nguyen
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Patent number: 9471844Abstract: Techniques are disclosed for creating a background model of a scene using both a pixel based approach and a context based approach. The combined approach provides an effective technique for segmenting scene foreground from background in frames of a video stream. Further, this approach can scale to process large numbers of camera feeds simultaneously, e.g., using parallel processing architectures, while still generating an accurate background model. Further, using both a pixel based approach and context based approach ensures that the video analytics system can effectively and efficiently respond to changes in a scene, without overly increasing computational complexity. In addition, techniques are disclosed for updating the background model, from frame-to-frame, by absorbing foreground pixels into the background model via an absorption window, and dynamically updating background/foreground thresholds.Type: GrantFiled: October 29, 2014Date of Patent: October 18, 2016Assignee: Behavioral Recognition Systems, Inc.Inventors: Kishor Adinath Saitwal, Lon Risinger, Wesley Kenneth Cobb
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Patent number: 9412027Abstract: A behavioral recognition system may include both a computer vision engine and a machine learning engine configured to observe and learn patterns of behavior in video data. Certain embodiments may be configured to detect and evaluate the presence of sea-surface oil on the water surrounding an offshore oil platform. The computer vision engine may be configured to segment image data into detected patches or blobs of surface oil (foreground) present in the field of view of an infrared camera (or cameras). A machine learning engine may evaluate the detected patches of surface oil to learn to distinguish between sea-surface oil incident to the operation of an offshore platform and the appearance of surface oil that should be investigated by platform personnel.Type: GrantFiled: August 11, 2015Date of Patent: August 9, 2016Assignee: Behavioral Recognition Systems, Inc.Inventor: Wesley Kenneth Cobb
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Patent number: 9373055Abstract: Techniques are disclosed for detecting sudden illumination changes using radiance consistency within a spatial neighborhood. A background/foreground (BG/FG) component of a behavior recognition system may be configured to generate a background image depicting a scene background. Further, the (BG/FG) component may periodically evaluate a current video frame to determine whether a sudden illumination change has occurred. A sudden illumination change occurs when scene lighting changes dramatically from one frame to the next (or over a small number of frames).Type: GrantFiled: December 16, 2008Date of Patent: June 21, 2016Assignee: Behavioral Recognition Systems, Inc.Inventors: Wesley Kenneth Cobb, Kishor Adinath Saitwal
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Patent number: 9349275Abstract: Techniques are disclosed for normalizing and publishing alerts using a behavioral recognition-based video surveillance system configured with an alert normalization module. Certain embodiments allow a user of the behavioral recognition system to provide the normalization module with a set of relative weights for alert types and a maximum publication value. Using these values, the normalization module evaluates an alert and determines whether its rareness value exceed a threshold. Upon determining that the alert exceeds the threshold, the module normalizes and publishes the alert.Type: GrantFiled: March 15, 2013Date of Patent: May 24, 2016Assignee: Behavorial Recognition Systems, Inc.Inventors: Kishor Adinath Saitwal, Wesley Kenneth Cobb
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Patent number: 9349054Abstract: Techniques are disclosed for creating a background model of a scene using both a pixel based approach and a context based approach. The combined approach provides an effective technique for segmenting scene foreground from background in frames of a video stream. Further, this approach can scale to process large numbers of camera feeds simultaneously, e.g., using parallel processing architectures, while still generating an accurate background model. Further, using both a pixel based approach and context based approach ensures that the video analytics system can effectively and efficiently respond to changes in a scene, without overly increasing computational complexity. In addition, techniques are disclosed for updating the background model, from frame-to-frame, by absorbing foreground pixels into the background model via an absorption window, and dynamically updating background/foreground thresholds.Type: GrantFiled: October 29, 2014Date of Patent: May 24, 2016Assignee: Behavioral Recognition Systems, Inc.Inventors: Kishor Adinath Saitwal, Lon Risinger, Wesley Kenneth Cobb
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Patent number: 9317908Abstract: Techniques are disclosed for analyzing a scene depicted in an input stream of video frames captured by a video camera. Bounding boxes are determined for a set foreground patches identified in a video frame. For each bounding box, the techniques include determining textures for first areas, each including a foreground pixel and surrounding pixels, and determining textures for second areas including pixels of the background model image corresponding to the pixels of the foreground areas. Further, for each foreground pixel in the bounding box area, a correlation score is determined based on the texture of the corresponding first area and second area. Pixels whose correlation scores exceed a threshold are removed from the foreground patch. The size of the bounding box may also be reduced to fit the modified foreground patch.Type: GrantFiled: June 28, 2013Date of Patent: April 19, 2016Assignee: Behavioral Recognition System, Inc.Inventors: Ming-Jung Seow, Tao Yang, Wesley Kenneth Cobb
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Patent number: 9142217Abstract: A system for facilitating free form dictation, including directed dictation and constrained recognition and/or structured transcription among users having heterogeneous protocols for generating, transcribing, and exchanging recognized and transcribed speech. The system includes a system transaction manager having a “system protocol,” to receive a speech information request from an authorized user. The speech information request is generated using a user interface capable of bi-directional communication with the system transaction manager and supporting dictation applications. A speech recognition and/or transcription engine (ASR), in communication with the system transaction manager, receives the speech information request, generates a transcribed response, and transmits the response to the system transaction manager. The system transaction manager routes the response to one or more of the users. In another embodiment, the system employs a virtual sound driver for streaming free form dictation to any ASR.Type: GrantFiled: June 27, 2013Date of Patent: September 22, 2015Assignee: Advanced Voice Recognition Systems, Inc.Inventors: Joseph H. Miglietta, Michael K. Davis
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Patent number: 8923609Abstract: A machine-learning engine is disclosed that is configured to recognize and learn behaviors, as well as to identify and distinguish between normal and abnormal behavior within a scene, by analyzing movements and/or activities (or absence of such) over time. The machine-learning engine may be configured to evaluate a sequence of primitive events and associated kinematic data generated for an object depicted in a sequence of video frames and a related vector representation. The vector representation is generated from a primitive event symbol stream and a phase space symbol stream, and the streams describe actions of the objects depicted in the sequence of video frames.Type: GrantFiled: April 2, 2013Date of Patent: December 30, 2014Assignee: Behavioral Recognition Systems, Inc.Inventors: John Eric Eaton, Wesley Kenneth Cobb, Dennis G. Urech, David S. Friedlander, Gang Xu, Ming-Jung Seow, Lon W. Risinger, David M. Solum, Tao Yang, Rajkiran K. Gottumukkal, Kishor Adinath Saitwal
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Patent number: 8797405Abstract: Techniques are disclosed for visually conveying classifications derived from pixel-level micro-features extracted from image data. The image data may include an input stream of video frames depicting one or more foreground objects. The classifications represent information learned by a video surveillance system. A request may be received to view a classification. A visual representation of the classification may be generated. A user interface may be configured to display the visual representation of the classification and to allow a user to view and/or modify properties associated with the classification.Type: GrantFiled: August 31, 2009Date of Patent: August 5, 2014Assignee: Behavioral Recognition Systems, Inc.Inventors: Wesley Kenneth Cobb, Bobby Ernest Blythe, David Samuel Friedlander, Rajkiran Kumar Gottumukkal, Kishor Adinath Saitwal, Ming-Jung Seow, Gang Xu
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Patent number: 8786702Abstract: Techniques are disclosed for visually conveying a percept. The percept may represent information learned by a video surveillance system. A request may be received to view a percept for a specified scene. The percept may have been derived from data streams generated from a sequence of video frames depicting the specified scene captured by a video camera. A visual representation of the percept may be generated. A user interface may be configured to display the visual representation of the percept and to allow a user to view and/or modify metadata attributes with the percept. For example, the user may label a percept and set events matching the percept to always (or never) result in alert being generated for users of the video surveillance system.Type: GrantFiled: August 31, 2009Date of Patent: July 22, 2014Assignee: Behavioral Recognition Systems, Inc.Inventors: Wesley Kenneth Cobb, Bobby Ernest Blythe, Rajkiran Kumar Gottumukkal, Ming-Jung Seow
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Publication number: 20140132786Abstract: A behavioral recognition system may include both a computer vision engine and a machine learning engine configured to observe and learn patterns of behavior in video data. Certain embodiments may provide image stabilization of a video stream obtained from a camera. An image stabilization module in the behavioral recognition system obtains a reference image from the video stream. The image stabilization module identifies alignment regions within the reference image based on the regions of the image that are dense with features. Upon determining that the tracked features of a current image is out of alignment with the reference image, the image stabilization module uses the most feature dense alignment region to estimate an affine transformation matrix to apply to the entire current image to warp the image into proper alignment.Type: ApplicationFiled: November 11, 2013Publication date: May 15, 2014Applicant: Behavioral Recognition Systems, Inc.Inventors: Kishor Adinath SAITWAL, Wesley Kenneth COBB, Tao YANG
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Patent number: 8705861Abstract: 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 objects of the background image. Statistically similar regions may be merged and associated. The regions are analyzed to determine their z-depth order in relation to a video capturing device providing the stream of the video frames and other regions, using occlusions between the regions and data about foreground objects in the scene. An annotated map describing the identified regions and their properties is created and updated.Type: GrantFiled: June 12, 2012Date of Patent: April 22, 2014Assignee: Behavioral Recognition Systems, Inc.Inventors: John Eric Eaton, Wesley Kenneth Cobb, Bobby Ernest Blythe, Rajkiran Kumar Gottumukkal, Kishor Adinath Saitwal
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Publication number: 20140050355Abstract: A behavioral recognition system may include both a computer vision engine and a machine learning engine configured to observe and learn patterns of behavior in video data. Certain embodiments may be configured to detect and evaluate the presence of sea-surface oil on the water surrounding an offshore oil platform. The computer vision engine may be configured to segment image data into detected patches or blobs of surface oil (foreground) present in the field of view of an infrared camera (or cameras). A machine learning engine may evaluate the detected patches of surface oil to learn to distinguish between sea-surface oil incident to the operation of an offshore platform and the appearance of surface oil that should be investigated by platform personnel.Type: ApplicationFiled: August 20, 2013Publication date: February 20, 2014Applicant: Behavioral Recognition Systems, Inc.Inventor: Wesley Kenneth COBB
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Patent number: 8625884Abstract: 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 least one cluster providing a statistical distribution of an event in the specified scene. Each statistical distribution may be derived from data streams generated from a sequence of video frames depicting the specified scene captured by a video camera. Each event may be observed to occur at a location in the specified scene corresponding to a location of the respective cluster in the event map. The event map may be configured to allow a user to view and/or modify properties associated with each cluster. For example, the user may label a cluster and set events matching the cluster to always (or never) generate an alert.Type: GrantFiled: August 18, 2009Date of Patent: January 7, 2014Assignee: Behavioral Recognition Systems, Inc.Inventors: Wesley Kenneth Cobb, Bobby Ernest Blythe, Rajkiran Kumar Gottumukkal, Ming-Jung Seow
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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
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Publication number: 20130346079Abstract: A system for facilitating free form dictation, including directed dictation and constrained recognition and/or structured transcription among users having heterogeneous protocols for generating, transcribing, and exchanging recognized and transcribed speech. The system includes a system transaction manager having a “system protocol,” to receive a speech information request from an authorized user. The speech information request is generated using a user interface capable of bi-directional communication with the system transaction manager and supporting dictation applications. A speech recognition and/or transcription engine (ASR), in communication with the system transaction manager, receives the speech information request, generates a transcribed response, and transmits the response to the system transaction manager. The system transaction manager routes the response to one or more of the users. In another embodiment, the system employs a virtual sound driver for streaming free form dictation to any ASR.Type: ApplicationFiled: June 27, 2013Publication date: December 26, 2013Applicant: Advanced Voice Recognition Systems, Inc.Inventors: Joseph H. Miglietta, Michael K. Davis
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Publication number: 20130339016Abstract: A system for facilitating free form dictation, including directed dictation and constrained recognition and/or structured transcription among users having heterogeneous protocols for generating, transcribing, and exchanging recognized and transcribed speech. The system includes a system transaction manager having a “system protocol,” to receive a speech information request from an authorized user. The speech information request is generated using a user interface capable of bi-directional communication with the system transaction manager and supporting dictation applications. A speech recognition and/or transcription engine (ASR), in communication with the system transaction manager, receives the speech information request, generates a transcribed response, and transmits the response to the system transaction manager. The system transaction manager routes the response to one or more of the users. In another embodiment, the system employs a virtual sound driver for streaming free form dictation to any ASR.Type: ApplicationFiled: June 27, 2013Publication date: December 19, 2013Applicant: Advanced Voice Recognition Systems, Inc.Inventors: Joseph H. Miglietta, Michael K. Davis
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Patent number: 8548198Abstract: 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 pixel-level micro-features that are extracted from the image data. Importantly, the discovery of the object type clusters 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. The SOM-ART network is adaptive and able to learn while discovering the object type clusters and classifying objects and identifying anomaly object types.Type: GrantFiled: September 18, 2012Date of Patent: October 1, 2013Assignee: Behavioral Recognition Systems, Inc.Inventors: Wesley Kenneth Cobb, David Friedlander, Rajkiran Kumar Gottumukkal, Ming-Jung Seow, Gang Xu