People recognition in multi-cameras using the visual color processing mechanism

• Published in: Neurocomputing (Amsterdam) 2016-05, Vol.188, p.71-81
• Main Authors: Lin, XiaoJin, Wu, QingXiang, Wang, Xuan, Zhuo, ZhiQiang, Zhang, GongRong
• Format: Article
• Language: English
• Subjects: Algorithms; Color; Feature extraction; Moving people recognition; Multi-camera video datasets; Neural networks; Recognition; Spiking; Spiking neural networks; State of the art; Support vector machine; Visual color processing
• ISSN: 0925-2312; 1872-8286
• DOI: 10.1016/j.neucom.2014.10.107

In this paper a people recognition algorithm is proposed, in which the color processing mechanism is inspired by the biological visual system. The algorithm is constructed in two parts. In the first part a spiking neural network is proposed to extract the color features of the people images which are captured from videos, and a set of new features is generated by fusing the color features and color moments. In the second part, after a feature reduction, a Support Vector Machine is trained and then used to recognize a specific people. The algorithm has been successfully applied to recognize people in CASIA Database with a high recognition rate. In order to evaluate performance and analyze characteristics of people recognition algorithms in multi-camera scenes, Multi-Camera Video (MCV) dataset is made in this paper. It is used to evaluate and analyze the proposed method and a set of characteristics of the proposed algorithms are obtained. Experimental results demonstrate that the algorithm is comparable to state-of-the-art approaches in terms of accuracy and the direction for further improvement of the proposed algorithm is provided.