Invention Grant
- Patent Title: Semantic representation module of a machine-learning engine in a video analysis system
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Application No.: US16545571Application Date: 2019-08-20
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Publication No.: US10706284B2Publication Date: 2020-07-07
- Inventor: 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
- Applicant: Avigilon Patent Holding 1 Corporation
- Applicant Address: CA Vancouver
- Assignee: AVIGILON PATENT HOLDING 1 CORPORATION
- Current Assignee: AVIGILON PATENT HOLDING 1 CORPORATION
- Current Assignee Address: CA Vancouver
- Agency: BakerHostetler
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06N20/00 ; G06F16/28 ; G06N3/04 ; G06N3/08 ; G06N3/00 ; G06K9/66 ; G06K9/62

Abstract:
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.
Public/Granted literature
- US20190377951A1 SEMANTIC REPRESENTATION MODULE OF A MACHINE-LEARNING ENGINE IN A VIDEO ANALYSIS SYSTEM Public/Granted day:2019-12-12
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