Adrien Descamps

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Crowd counting and density estimation is still one of the important task in video surveillance. Usually a regression based method is used to estimate the number of people from a sequence of images. In this paper we investigate to estimate the count of people in a crowded scene. We detect the head region since this is the most visible part of the body in a(More)
In this paper, we address the problem of person detection in indoor videosurveillance data. We present a new method based on the state of the art integral channel features. This approach is extended to allow the use of temporal features in addition to appearance based features. The temporal features are integrated by a robust background subtraction method.(More)
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