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Currently, Compressive Tracking (CT) method has drawn great attention because of its high efficiency. However, it cannot well deal with some appearance variations due to its limitations of feature expression and it only uses a fixed parameter to update the appearance model. In order to handle such matters, we propose an adaptive CT method that combines the predicted target position with CT based on...
In this paper, we investigate a novel algorithm to the problem of interactive image segmentation. We propose an extension of the Growcut framework using the Tumors Automata (TA) formed from the superpixel. The proposed TA is similar to Cellular Automata but can directly deal with superpixel. The superpixels (image segments) can provide powerful boundary cues to guide segmentation, where superpixels...
Tracking multiple moving targets in a video is a challenge because of several factors, including noisy video data, varying number of targets, and mutual occlusion problems. The Gaussian mixture probability hypothesis density (GM-PHD) filter, which aims to recursively propagate the intensity associated with the multi-target posterior density, can overcome the difficulty caused by the data association...
Tracking humans in video is a challenge because of data association and mutual occlusion problems. This paper presents a Gaussian mixture probability hypothesis density-based visual tracking system with game-theoretical occlusion handling. First, a two-step occlusion reasoning algorithm is proposed to determine the occlusion region. Then, an improved spatial color appearance with interferences by...
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