Real-Time crowd density estimation using images

Authors:
A. N. Marana;M. A. Cavenaghi;R. S. Ulson;F. L. Drumond
Affiliations:
DCo (Department of Computing) – LCAD (Laboratory of High Performance Computing), UNESP (Sao Paulo State University) – FC (School of Sciences), Bauru, SP, Brazil;DCo (Department of Computing) – LCAD (Laboratory of High Performance Computing), UNESP (Sao Paulo State University) – FC (School of Sciences), Bauru, SP, Brazil;DCo (Department of Computing) – LCAD (Laboratory of High Performance Computing), UNESP (Sao Paulo State University) – FC (School of Sciences), Bauru, SP, Brazil;DCo (Department of Computing) – LCAD (Laboratory of High Performance Computing), UNESP (Sao Paulo State University) – FC (School of Sciences), Bauru, SP, Brazil
Venue:
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Year:
2005

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Abstract

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.