An improved eLBPH method for facial identity recognition: Expression-specific weighted local binary pattern histogram

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	An improved eLBPH method for facial identity recognition: Expression-specific weighted local binary pattern histogram
	Xi, Xuanyang; Qin, Zhengke; Ding, Shuguang; Qiao, Hong
	2015-12
会议名称	Robotics and Biomimetics (ROBIO), 2015 IEEE International Conference on
会议日期	6-9 Dec. 2015
会议地点	Zhuhai, China
摘要	Face perception is one of the most important tasks in robot vision especially for service robots. The spatially enhanced local binary pattern histogram (eLBPH) method has been proved to be effective for facial image representation and analysis, but the expression factor isn't considered and the region-dividing method is rough. In this paper, inspired by the biological mechanism of human memory and face perception, we improve the eLBPH and propose a new method, expression-specific weighted local binary pattern histogram (EWLBPH). Accordingly, the new method introduces a semantic division process and an extended modulation process into the classical eLBPH. What's more, for the facial expression recognition, we propose a novel method which utilizes the convolutional deep belief network (CDBN) to extract discriminative information and represent them effectively. Finally, through experiments we verify the rationality and effectiveness of the improvement and two psychophysical findings.
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/14764
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
通讯作者	Xi, Xuanyang
作者单位	Institute of Automaton, Chinese Academy of Science
推荐引用方式 GB/T 7714	Xi, Xuanyang,Qin, Zhengke,Ding, Shuguang,et al. An improved eLBPH method for facial identity recognition: Expression-specific weighted local binary pattern histogram[C],2015.

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