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In this paper, we address the problem of vehicle detection and tracking with low-angle cameras by combining windshield detection and feature points clustering, effectively fusing several primitive image features such as color, edge and interest point. By exploring various heterogenous features and multiple vehicle models, we achieve at least two improvements over the existing methods: higher detection...
In this paper, we propose a novel approach that combines particle filter tracking and 3D graph cut based segmentation to achieve silhouette tracking against drastic scale change and occlusion. The segmentation module offers particle filter tracking procedure the target shape information to compensate spatial information loss in the histogram based particle filter tracking process. Meanwhile, particle...
Major problem of tracking a visual target in occurrence of out-of-field-of-view is unable to obtain information of the target from image frame. We solve this problem by utilizing background information in the image frame. Scenes of tracking a car from an observer in aerial vehicle have been employed. Background information is obtained from road area, building area, and the others. Prior probabilities...
In this paper, we propose a new algorithm for optimally adapting ellipses outlining objects of interest in order to improve the performance of a colour based tracking approach for real video sequences. We present a Lagrangian based method to integrate a regularising component into the covariance matrix to be computed. Technically, we intend to reduce the residuals between the estimated probability...
In this paper, we describe a new approach to improve the video based object tracking system with particle filter using shape similarity. It deals with single object tracking whose dynamics age highly non-linear. The shape similarity between a template and estimated regions in the video sequences can be measured by their normalized cross-correlation of distance transformation. Here within this present...
Robust and real-time object tracking of any objects is a challenging task. Particle filtering has been proven very successful for non-gaussian and non-linear estimation problems. This paper describes a new approach to improve the moving object tracking system with particle filter using shape similarity. The shape similarity between a template and estimated regions in the video sequences can be measured...
Chang detection is one of the most important research issues in the field of video processing. This paper presents an adaptive method of objects and shadows detection in video streams based on the HSI color space. Bi-models of background is set up via the minimum, the maximum and the largest interframe absolute difference of per static pixel, which are adaptively updated by synthesizing pixel level,...
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