Object tracking in video with visual constraints
First Claim
1. A computer-implemented method for tracking an object in a frame of a video, comprising:
- (a) determining an adaptive term value based on an adaptive model and at least a portion of the frame, wherein the adaptive model is determined based on at least one previous frame of the video;
(b) determining a pose constraint value based on a pose model and at least a portion the frame, wherein the pose model is determined based on different possible appearances of the object;
(c) determining an alignment confidence score based on an alignment model and at least a portion the frame, wherein the alignment model detects misalignments of the tracked object;
(d) determining an energy value based on the adaptive term value, the pose constraint value, and the alignment confidence score; and
(e) determining a resultant tracking state based on the energy value, the resultant tracking state defining a likely position of the object in the frame given the object'"'"'s likely position in a set of previous frames in the video.
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Accused Products
Abstract
Embodiments of the present invention relate to object tracking in video. In an embodiment, a computer-implemented method tracks an object in a frame of a video. An adaptive term value is determined based on an adaptive model and at least a portion of the frame. A pose constraint value is determined based on a pose model and at least a portion the frame. An alignment confidence score is determined based on an alignment model and at least a portion the frame. Based on the adaptive term value, the pose constraint value, and the alignment confidence score, an energy value is determined. Based on the energy value, a resultant tracking state is determined. The resultant tracking state defines a likely position of the object in the frame given the object'"'"'s likely position in a set of previous frames in the video.
30 Citations
24 Claims
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1. A computer-implemented method for tracking an object in a frame of a video, comprising:
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(a) determining an adaptive term value based on an adaptive model and at least a portion of the frame, wherein the adaptive model is determined based on at least one previous frame of the video; (b) determining a pose constraint value based on a pose model and at least a portion the frame, wherein the pose model is determined based on different possible appearances of the object; (c) determining an alignment confidence score based on an alignment model and at least a portion the frame, wherein the alignment model detects misalignments of the tracked object; (d) determining an energy value based on the adaptive term value, the pose constraint value, and the alignment confidence score; and (e) determining a resultant tracking state based on the energy value, the resultant tracking state defining a likely position of the object in the frame given the object'"'"'s likely position in a set of previous frames in the video. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A system for tracking an object in a frame of a video, comprising:
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a pose constraint module that determines a pose constraint value based on a pose model and at least a portion the frame; an alignment constraint module that determines an alignment confidence score based on an alignment model and at least a portion the frame; an adaptive module that determines an adaptive term value based on an adaptive model and at least a portion of a frame in the video; a visual constrainer that determines an energy value based on the adaptive term value, the pose constraint value, and the alignment confidence score; and a tracker that determines a resultant tracking state based on the energy value, the resultant tracking state defining a likely position of the object in the frame given the object'"'"'s likely position in a set of previous frames in the video, wherein the adaptive model is determined based on at least one previous frame of the video, wherein the pose model is determined based on different possible appearances of the object, and wherein the alignment model detects misalignments of the tracked object. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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Specification