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We present a method for object tracking over time sequence imagery. The image plane is represented with a 4-connected planar graph where vertices are associated with pixels. On each image, the outer contour of the object is localized by finding the optimal cycle in the graph such that a cost function based on temporal, appearance and shape priors is minimized. Our contribution is the particle filtering-based...
The automatic objects tracking in videos plays important roles in computer vision applications. In this paper, we propose an automatic object tracking method hybrid with GMM and edge orientation histogram based CamShift. GMM is applied to detect objects motion. Different moving objects are separated by connected component analysis. And CamShift is processed by using edge orientation histogram to track...
Object tracking is an important computer vision problem with many civilian and military applications including surveillance, robotics and intelligent vehicle design. Most of these applications require fast processing due to their real time nature. The Cell processor is a cost-efficient commodity architecture intended for video gaming and provides new opportunities for parallel processing. This paper...
Object tracking is one of the major subjects in machine vision and plays a main role in detection of major events in indoor soccer matches. In this paper, a novel approach for tracking the ball and players is proposed. In this method, the ground lines are segmented and eliminated using a fast and effective method. Then, the remaining non-field pixels are considered and labeled as players and the ball...
Matching is a central problem in pattern recognition and computer vision, its applications includes object detection and tracking. HCMA (hierarchical chamfer matching) is a classical image matching algorithm, which utilizes the edge information to match the images robustly and the multi-resolution pyramid to accelerate the matching process. However, for images with cluttered background and high resolution,...
Object tracking in computer vision is important. Numerous research papers have been published about this problem. Few references relating to tracking shaped objects via the Hough Transforms exist. This paper provides a method based on the Standard Hough Transform to track rectangular objects. Our method works on edge images obtained by applying the Canny edge detector to the source image. The rectangular...
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