2005 | OriginalPaper | Buchkapitel
Real-Time Crowd Density Estimation Using Images
verfasst von : A. N. Marana, M. A. Cavenaghi, R. S. Ulson, F. L. Drumond
Erschienen in: Advances in Visual Computing
Verlag: Springer Berlin Heidelberg
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This paper presents a technique for real-time crowd density estimation based on textures of crowd images. In this technique, the current image from a sequence of input images is classified into a crowd density class. Then, the classification is corrected by a low-pass filter based on the crowd density classification of the last
n
images of the input sequence. The technique obtained 73.89% of correct classification in a real-time application on a sequence of 9892 crowd images. Distributed processing was used in order to obtain real-time performance.