Robust object tracking system
First Claim
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1. A method for tracking objects, comprising:
- identifying a target;
identifying a plurality of auxiliary objects related to the target; and
tracking the target using the plurality of auxiliary objects,wherein a data mining technique is used to identify the plurality of auxiliary objects related to the target, the data mining technique further comprising;
using a frequent pattern growth (FP growth) technique to select a plurality of candidate auxiliary objects with high co-occurrent frequency with the target; and
selecting the plurality of auxiliary objects from the plurality of candidate auxiliary objects,wherein each of the plurality of auxiliary objects maintains a high motion correlation with the target.
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Abstract
A method for tracking objects includes identifying a target, identifying a plurality of auxiliary objects related to the target, and tracking the target using the plurality of auxiliary objects.
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Citations
8 Claims
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1. A method for tracking objects, comprising:
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identifying a target; identifying a plurality of auxiliary objects related to the target; and tracking the target using the plurality of auxiliary objects, wherein a data mining technique is used to identify the plurality of auxiliary objects related to the target, the data mining technique further comprising; using a frequent pattern growth (FP growth) technique to select a plurality of candidate auxiliary objects with high co-occurrent frequency with the target; and selecting the plurality of auxiliary objects from the plurality of candidate auxiliary objects, wherein each of the plurality of auxiliary objects maintains a high motion correlation with the target. - View Dependent Claims (2, 3, 4)
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5. A tracking system configured to:
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receive an image sequence; identify a target in the image sequence; identify a plurality of auxiliary objects related to the target; and
track the target using the plurality of auxiliary objects,wherein a data mining technique is used to identify the plurality of auxiliary objects related to the target, the data mining technique further comprising; using a frequent pattern growth (FP growth) technique to select a plurality of candidate auxiliary objects with high co-occurrent frequency with the target; and selecting the plurality of auxiliary objects from the plurality of candidate auxiliary objects, wherein each of the plurality of auxiliary objects maintains a high motion correlation with the target. - View Dependent Claims (6, 7, 8)
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Specification