Real-time object analysis with occlusion handling
First Claim
1. A method, comprising the steps of:
- receiving a video sequence comprising detection results from one or more detectors, the detection results identifying one or more objects;
applying a clustering framework to the detection results to identify one or more clusters associated with the one or more objects, wherein the clustering framework is applied to the video sequence on a frame-by-frame basis;
determining spatial and temporal information for each of the one or more clusters;
associating the one or more clusters to the detection results based on the spatial and temporal information in consecutive frames of the video sequence to generate tracking information;
generating one or more target tracks based on the tracking information for the one or more clusters; and
consolidating the one or more target tracks to generate refined tracks for the one or more objects;
wherein the steps are performed by at least one processor device coupled to a memory.
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Accused Products
Abstract
A method includes the following steps. A video sequence including detection results from one or more detectors is received, the detection results identifying one or more objects. A clustering framework is applied to the detection results to identify one or more clusters associated with the one or more objects. The clustering framework is applied to the video sequence on a frame-by-frame basis. Spatial and temporal information for each of the one or more clusters are determined. The one or more clusters are associated to the detection results based on the spatial and temporal information in consecutive frames of the video sequence to generate tracking information. One or more target tracks are generated based on the tracking information for the one or more clusters. The one or more target tracks are consolidated to generate refined tracks for the one or more objects.
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Citations
20 Claims
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1. A method, comprising the steps of:
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receiving a video sequence comprising detection results from one or more detectors, the detection results identifying one or more objects; applying a clustering framework to the detection results to identify one or more clusters associated with the one or more objects, wherein the clustering framework is applied to the video sequence on a frame-by-frame basis; determining spatial and temporal information for each of the one or more clusters; associating the one or more clusters to the detection results based on the spatial and temporal information in consecutive frames of the video sequence to generate tracking information; generating one or more target tracks based on the tracking information for the one or more clusters; and consolidating the one or more target tracks to generate refined tracks for the one or more objects; wherein the steps are performed by at least one processor device coupled to a memory. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. An apparatus, comprising:
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a memory; and a processor operatively coupled to the memory and configured to; receive a video sequence comprising detection results from one or more detectors, the detection results identifying one or more objects; apply a clustering framework to the detection results to identify one or more clusters associated with the one or more objects, wherein the clustering framework is applied to the video sequence on a frame-by-frame basis; determine spatial and temporal information for each of the one or more clusters; associate the one or more clusters to the detection results based on the spatial and temporal information in consecutive frames of the video sequence to generate tracking information; generate one or more target tracks based on the tracking information for the one or more clusters; and consolidate the one or more target tracks to generate refined tracks for the one or more objects. - View Dependent Claims (15, 16, 17, 18, 19)
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20. An article of manufacture comprising a computer readable storage medium for storing computer readable program code which, when executed, causes a computer to:
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receive a video sequence comprising detection results from one or more detectors, the detection results identifying one or more objects; apply a clustering framework to the detection results to identify one or more clusters associated with the one or more objects, wherein the clustering framework is applied to the video sequence on a frame-by-frame basis; determine spatial and temporal information for each of the one or more clusters; associate the one or more clusters to the detection results based on the spatial and temporal information in consecutive frames of the video sequence to generate tracking information; generate one or more target tracks based on the tracking information for the one or more clusters; and consolidate the one or more target tracks to generate refined tracks for the one or more objects.
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Specification