Abstract: Various embodiments are disclosed for performing object tracking. One embodiment is a system for tracking an object in a plurality of frames, comprising a probability map generator configured to generate a probability map by estimating probability values of pixels in the frame, wherein the probability of each pixel corresponds to a likelihood of the pixel being located within the object. The system further comprises a contour model generator configured to identify a contour model of the object based on a temporal prediction method, a contour weighting map generator configured to derive a contour weighting map based on thickness characteristics of the contour model, a tracking refinement module configured to refine the probability map according to weight values specified in the contour weighting map, and an object tracker configured to track a location of the object within the plurality of frames based on the refined probability map.

Abstract: Disclosed are various embodiments for the selection of an object boundary shown in an image. An initial boundary probability map of an image is generated by one or more computing devices. A first input path segment is obtained, and a selection path is generated based on the first input path segment and the initial boundary probability map. A weighted boundary probability map is generated based on the selection path. A second input path segment is obtained, and a replacement selection path is generated based on the weighted boundary probability map and the second input path segment.

Abstract: Various embodiments are disclosed for performing object tracking. One embodiment is a system for tracking an object in a plurality of frames, comprising a probability map generator configured to generate a probability map by estimating probability values of pixels in the frame, wherein the probability of each pixel corresponds to a likelihood of the pixel being located within the object. The system further comprises a contour model generator configured to identify a contour model of the object based on a temporal prediction method, a contour weighting map generator configured to derive a contour weighting map based on thickness characteristics of the contour model, a tracking refinement module configured to refine the probability map according to weight values specified in the contour weighting map, and an object tracker configured to track a location of the object within the plurality of frames based on the refined probability map.

Abstract: Disclosed are various embodiments for the selection of an object boundary shown in an image. An initial boundary probability map of an image is generated by one or more computing devices. A first input path segment is obtained, and a selection path is generated based on the first input path segment and the initial boundary probability map. A weighted boundary probability map is generated based on the selection path. A second input path segment is obtained, and a replacement selection path is generated based on the weighted boundary probability map and the second input path segment.