Abstract To improve the efficiency of traditional face alignment algorithms, a face alignment algorithm based on shape parametric regression is proposed. Firstly, face is constrained by face shape space and face shape is depicted by a low dimensional shape parameter. Then, a series of shape parameter regressions is learned under the framework of a two-level shape parameter regression algorithm with the combination of an efficient explicit shape feature index method and multiple random feature selection method. Finally, the alignment face shape is portrayed. By the proposed algorithm, the amount of data storage is reduced and the speed of the face alignment is improved. Experiments on complex dataset show that the proposed algorithm obtains good results. Moreover, it can be applied directly on mobile phones, tablet composters and other low-end devices.
About author:: (PENG Mingchao， born in 1990， master student. His research interests include pattern recognition and intelligent robot.)(BAO Jiao(Corresponding author)， born in 1982，Ph.D. candidate. Her research interests include artificial intelligence.)(YE Mao， born in 1973， Ph.D.， professor. His research interests include pattern recognition and computer vision.)(GOU Qunsen， born in 1990， master student. His research interests include pattern recognition.)(WANG Mengwei， born in 1993， master student. His research interests include pattern recognition.)
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2016, Vol. 29 
