Pedestrians Crowd Segmentation Based on Bayesian Formulation

DOI

10.2991/ameii-15.2015.3How to use a DOI?

Keywords

Bayesian Formulation; head detection; Pedestrian Crowd Segmentation.

Abstract

Crowd people segmentation algorithm in complex environments is proposed based on Bayesian formula. In this method solved the case of the occlusion of crowd pedestrian which are difficult to detect one pedestrian from each other. This algorithm uses the Bayesian formula to convert the problem that how to segmentation the crowd people into seeking maximum a posterior probability. Using the assumption segmentation model of the pedestrian to match the foreground area, and then modify segmentation model for converging to the maximum posterior probability through multiple iterations. Experiments result that using the PETS 2009 video database show that this algorithm can effectively and accurately detect the pedestrian whose occlusion is less half and the part of severely blocked pedestrians can also be identification.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yun Liu
AU  - Guangpeng Ma
PY  - 2015/04
DA  - 2015/04
TI  - Pedestrians Crowd Segmentation Based on Bayesian Formulation
BT  - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
PB  - Atlantis Press
SP  - 16
EP  - 21
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-15.2015.3
DO  - 10.2991/ameii-15.2015.3
ID  - Liu2015/04
ER  -