VIDEO OBJECT FRAGMENTATION DETECTION AND MANAGEMENT
First Claim
1. A computer-implemented method of determining a current spatial representation for a detection in a current frame of an image sequence, said method comprising the steps of:
- deriving an expected spatial representation for said detection based on at least one previous frame;
generating a spatial representation of said detection;
extending said spatial representation to obtain an extended spatial representation, based on the expected spatial representation;
determining a similarity measure between said extended spatial representation and said expected spatial representation; and
determining the current spatial representation for the detection based on said similarity measure.
1 Assignment
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Accused Products
Abstract
Disclosed herein are a computer-implemented method and a camera system for determining a current spatial representation for a detection in a current frame of an image sequence. The method derives an expected spatial representation (820) for the detection based on at least one previous frame, generates a spatial representation (810) of the detection, and extends the spatial representation (810) to obtain an extended spatial representation (830), based on the expected spatial representation (820). The method determines a similarity measure between the extended spatial representation (830) and the expected spatial representation (820), and then determines the current spatial representation for the detection to based on the similarity measure.
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Citations
19 Claims
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1. A computer-implemented method of determining a current spatial representation for a detection in a current frame of an image sequence, said method comprising the steps of:
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deriving an expected spatial representation for said detection based on at least one previous frame; generating a spatial representation of said detection; extending said spatial representation to obtain an extended spatial representation, based on the expected spatial representation; determining a similarity measure between said extended spatial representation and said expected spatial representation; and determining the current spatial representation for the detection based on said similarity measure. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A computer-implemented method of associating at least one of a plurality of detections in a frame of an image sequence with a track, said method comprising the steps of:
for each one of said plurality of detections; determining an initial spatial similarity measure between an expected spatial representation associated with said track and a spatial representation of said detection; determining an extended similarity measure between said expected spatial representation of said track and an extended spatial representation of said detection; and associating said detection with said track, based on at least one of; (i) said initial spatial similarity measure exceeding a direct association threshold; and (ii) said extended similarity measure exceeding a fragment similarity threshold. - View Dependent Claims (9, 10, 11, 12)
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13. A camera system for classifying a detection in a frame of an image sequence as a fragment of a video object in said frame, based on a spatial similarity between said detection and an expected spatial representation for a track associated with said image sequence, said camera system comprising:
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a lens system; a camera module coupled to said lens system to capture at least one frame in said image sequence; a storage device for storing a computer program; and a processor for executing the program, said program comprising; code for deriving an extended spatial representation from a spatial representation of said detection, wherein at least one dimension of said extended spatial representation is at least as large as a corresponding dimension of said expected spatial representation; code for determining an extended spatial similarity measure between said extended spatial representation and said expected spatial representation; and code for determining said detection to be a fragment of said video object, if the extended spatial similarity measure exceeds a fragment similarity threshold. - View Dependent Claims (14)
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15. A computer-implemented method of associating an association hypothesis with a track associated with an image, based on a plurality of fragments detected in said image, said method comprising the steps of:
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generating a plurality of association hypotheses based on said track and said plurality of fragments, each association hypothesis including an expectation associated with said track and a combination of at least one fragment associated with said expectation; for each association hypothesis, performing the steps of; determining a matching similarity score, based on said expectation and at least one characteristic of at least one fragment in the combination of the association hypothesis; and adjusting the matching similarity score, based on a number of fragments in the combination of the association hypothesis; selecting an association hypothesis from said plurality of association hypotheses, based on the adjusted matching similarity scores of the association hypotheses; and associating said selected association hypothesis with said track. - View Dependent Claims (16, 17)
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18. A computer-implemented method of associating an association hypothesis with a track associated with an image, based on a fragment detected in said image and a plurality of tracks associated with said image, said method comprising the steps of:
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generating a plurality of association hypotheses based on said fragment and said plurality of tracks, each association hypothesis including said fragment detection and a combination of at least one expectation associated with said detection, wherein each expectation is associated with one of said tracks; for each association hypothesis, performing the steps of; determining a similarity score for each association hypothesis, based on said fragment detection and at least one characteristic of at least one track in the combination of the association hypothesis; and adjusting the similarity score, based on a number of track expectations included in the hypothesis; selecting an association hypothesis, based on the similarity scores for the association hypotheses; and associating said selected association hypothesis with said track.
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19. A method of determining a detection to be a fragment of a video object in a video frame sequence, based on a spatial similarity between a track associated with said video frame sequence and said detection in a video frame of said video frame sequence, said method comprising the steps of:
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deriving an extended spatial representation from a spatial representation of said detection, wherein at least one dimension of said extended spatial representation is at least as large as a corresponding dimension of an expected spatial representation of said track; determining an extended spatial similarity measure between said extended spatial representation and said expected spatial representation; and determining said detection to be a fragment of said video object when said extended spatial similarity measure exceeds an extended representation similarity threshold.
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Specification