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In a visual surveillance system, robust tracking of moving objects which are partially or even fully occluded is very difficult. In this paper, we present a method of tracking objects through occlusions using a combination of Kalman filter and color histogram. By changing covariance of process noise and measurement noise in Kalman filter, this method can maintain the tracking of moving objects before,...
In the fields of intelligent video surveillance, video analysis and computer vision, moving objects detection is one of the fundamental tasks. In this paper, we present an algorithm for moving objects detection based on Gaussian mixture model and iterative division, which can be used for real time processing. We use iterative division algorithm to filter illumination variation and local variations...
In this paper, an improved Camshift algorithm based on dynamic background is presented, detecting motion objects with Twice-Frame-Difference Method (TFDM) and tracking objects with Multi-Features-Fusion Method (MFFM). By the comparing experiments, the presented improved algorithm can acquire the better detecting effects and improve the robustness and accuracy of tracking.
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