Detection and Tracking of Moving Objects from a Moving Platform in Presence of Strong Parallax
First Claim
1. A computer-implemented method for detecting motion in a sequence of video frames, the method comprising:
- identifying residual pixels from the sequence of video frames, to provide estimated indication of a moving object or a static three-dimensional (3-D) structure; and
sorting the identified residual pixels to isolate pixels that correspond to the moving object comprising;
applying at least two geometric constraints to the identified one or more residual pixels, wherein the at least two geometric constraints represent at least a variation in relative depth of the residual pixels;
detecting a disparity of the residual pixels to the applied at least two geometric constraints;
based on the detected disparity, filtering the residual pixels to remove pixels that do not correspond to the moving object;
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Abstract
Among other things, methods, systems and computer program products are described for detecting and tracking a moving object in a scene. One or more residual pixels are identified from video data. At least two geometric constraints are applied to the identified one or more residual pixels. A disparity of the one or more residual pixels to the applied at least two geometric constraints is calculated. Based on the detected disparity, the one or more residual pixels are classified as belonging to parallax or independent motion and the parallax classified residual pixels are filtered. Further, a moving object is tracked in the video data. Tracking the object includes representing the detected disparity in probabilistic likelihood models. Tracking the object also includes accumulating the probabilistic likelihood models within a number of frames during the parallax filtering. Further, tracking the object includes based on the accumulated probabilistic likelihood models, extracting an optimal path of the moving object.
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Citations
25 Claims
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1. A computer-implemented method for detecting motion in a sequence of video frames, the method comprising:
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identifying residual pixels from the sequence of video frames, to provide estimated indication of a moving object or a static three-dimensional (3-D) structure; and sorting the identified residual pixels to isolate pixels that correspond to the moving object comprising; applying at least two geometric constraints to the identified one or more residual pixels, wherein the at least two geometric constraints represent at least a variation in relative depth of the residual pixels; detecting a disparity of the residual pixels to the applied at least two geometric constraints; based on the detected disparity, filtering the residual pixels to remove pixels that do not correspond to the moving object; - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 17, 24, 25)
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12. A computer program product, embodied on a computer readable medium, operable to cause a data processing apparatus to perform operations comprising:
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identify one or more residual pixels from video data; apply at least two geometric constraints to the identified one or more residual pixels; detect a disparity of the one or more residual pixels to the applied at least two geometric constraints; based on the detected disparity, classify the one or more residual pixels as belonging to parallax or independent motion and filtering the parallax classified residual pixels; and track a moving object in the video data comprising; representing the detected disparity in probabilistic likelihood models; accumulating the probabilistic likelihood models within a number of frames during the parallax filtering; and based on the accumulated probabilistic likelihood models, extracting an optimal path of the moving object. - View Dependent Claims (13, 14, 15, 16)
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18. A pipeline processing system comprising:
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a geometric constraint estimation stage to perform an estimation of multi-view geometric constraints based on feature point correspondences extracted from a sequence of video frames; a homography-based image detection stage to compute a background model image, and identify one or more residual pixels in the sequence of video frames based on inconsistencies with the background model; and a parallax filtering stage to filter out parallax pixels from the residual pixels by applying one or more outlier detection methods to disparity values with respect to each geometric constraint - View Dependent Claims (19, 20, 21, 22)
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23. A method for detecting motion in a sequence of video frames comprising:
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identifying from the sequence of video frames pixels associated with an object in actual motion or a static object in apparent motion; and processing the identified pixels to isolate the pixels associated with actual motion, wherein the isolating comprises; detecting a variation in relative depth of each identified pixels; based on the detected variation, identifying pixels that exceed a level of variation associated with the static structure; and filtering out those pixels that do not exceed the level of variation associated with the static structure.
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Specification