Semantic representation module of a machine-learning engine in a video analysis system
First Claim
1. A computer-implemented method for processing data describing a scene depicted in a sequence of video frames, the method comprising:
- receiving input data describing one or more objects detected in the scene, wherein the input data includes at least a classification for each of the one or more objects;
identifying one or more primitive events, wherein each primitive event provides a semantic value describing a behavior engaged in by a corresponding one of the objects depicted in the sequence of video frames and wherein each primitive event has an assigned primitive event symbol;
generating, for one or more objects, a primitive event symbol stream which includes the primitive event symbols corresponding to the primitive events identified for a respective object;
forming a first vector representation of each object based on the primitive event symbol stream for each respective object; and
analyzing the first vector representations to identify patterns of behavior for each object classification from the first vector representation.
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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.
55 Citations
24 Claims
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1. A computer-implemented method for processing data describing a scene depicted in a sequence of video frames, the method comprising:
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receiving input data describing one or more objects detected in the scene, wherein the input data includes at least a classification for each of the one or more objects; identifying one or more primitive events, wherein each primitive event provides a semantic value describing a behavior engaged in by a corresponding one of the objects depicted in the sequence of video frames and wherein each primitive event has an assigned primitive event symbol; generating, for one or more objects, a primitive event symbol stream which includes the primitive event symbols corresponding to the primitive events identified for a respective object; forming a first vector representation of each object based on the primitive event symbol stream for each respective object; and analyzing the first vector representations to identify patterns of behavior for each object classification from the first vector representation. - 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 describing a scene depicted in a sequence of video frames, comprising:
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receiving input data describing one or more objects detected in the scene, wherein the input data includes at least a classification for each of the one or more objects; identifying one or more primitive events, wherein each primitive event provides a semantic value describing a behavior engaged in by a corresponding one of the objects depicted in the sequence of video frames and wherein each primitive event has an assigned primitive event symbol; generating, for one or more of the objects, a primitive event symbol stream which includes the primitive event symbols corresponding to the primitive events identified for a respective object; forming a first vector representation of each object based on the primitive event symbol stream for each respective object; and passing the first vector representations to a machine learning engine configured to identify patterns of behavior for each object classification from the first vector representation. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. 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 including at least a classification for each of one or more objects in a sequence of the video frames; identify one or more primitive events, wherein each primitive event provides a semantic value describing a behavior engaged in by a corresponding one of the objects depicted in the sequence of video frames and wherein each primitive event has an assigned primitive event symbol; generate, for one or more of the objects, a primitive event symbol stream which includes the primitive event symbols corresponding to the primitive events identified for a respective object; form a first vector representation of each object based on the primitive event symbol stream for each respective object; and analyze the first vector representations to identify patterns of behavior for each object classification from the first vector representation. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24)
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Specification