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Numerous occurrences of stampedes in crowded situations have indicated that crowded people management is a daunting task. Therefore, people counting becomes a crucial component in visual surveillance mainly for capacity forecasting and security monitoring. We present an occlusion sensitive method for counting crowded people in congested situations to reduce the occurrences of catastrophic stampedes and crammed events. First, we adopt the Frame Difference Method and an improved Gaussian Mixture M
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