Semantic representation module of a machine-learning engine in a video analysis system
First Claim
1. A computer-implemented method for processing data related to a scene depicted in a sequence of video frames, the method comprising:
- receiving input data describing an object detected in the scene, wherein the input data comprises at least a classification for the object;
identifying one or more primitive events, related to a behavior engaged in by the object detected in the scene and wherein each primitive event has an assigned primitive event symbol;
generating, for the object, a primitive event symbol stream;
forming a first vector representing the object; and
comparing the first vector to a stored vector to define a similarity measure.
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Accused Products
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.
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Citations
20 Claims
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1. A computer-implemented method for processing data related to a scene depicted in a sequence of video frames, the method comprising:
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receiving input data describing an object detected in the scene, wherein the input data comprises at least a classification for the object; identifying one or more primitive events, related to a behavior engaged in by the object detected in the scene and wherein each primitive event has an assigned primitive event symbol; generating, for the object, a primitive event symbol stream; forming a first vector representing the object; and comparing the first vector to a stored vector to define a similarity measure. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A non-transitory computer-readable medium containing a program, which, when executed on a processor is configured to perform an operation for processing data related to a scene depicted in a sequence of video frames, comprising:
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receiving input data describing an object detected in the scene, wherein the input data comprises at least a classification for the object; identifying one or more primitive events, related to a behavior engaged in by the object detected in the scene and wherein each primitive event has an assigned primitive event symbol; generating, for the object, a primitive event symbol stream; forming a first vector representing the object; and comparing the first vector to a stored vector to define a similarity measure. - View Dependent Claims (10, 11, 12, 13)
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14. A system, comprising:
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a video input source; a processor; and a memory storing computer instructions, which, when executed on the processor configure the processor to; input data describing a scene depicted in a sequence of video frames, the input data comprises at least a classification for an object in a scene; identify one or more primitive events, wherein each primitive event provides a semantic value describing a behavior engaged in by the object depicted in the scene and wherein each primitive event has an assigned primitive event symbol; generate, for the object, a primitive event symbol; form a first vector representing the object; and compare the first vector to a stored vector to define a similarity measure. - View Dependent Claims (15, 16, 17, 18, 19, 20)
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Specification