ELM based smile detection using Distance Vector

被引:30
作者
Cui, Dongshun [1 ,2 ]
Huang, Guang-Bin [2 ]
Liu, Tianchi [2 ]
机构
[1] Nanyang Technol Univ, Interdisciplinary Grad Sch, Energy Res Inst NTU ERI N, Singapore 639798, Singapore
[2] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
关键词
Smile detection; Pair-wise Distance Vector; Extreme Learning Machine; EXTREME LEARNING-MACHINE; FACIAL EXPRESSION RECOGNITION; FACE DETECTION; CROSS-VALIDATION; ALIGNMENT; MODEL;
D O I
10.1016/j.patcog.2018.02.019
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Smile is one of the most common facial expressions, and it serves as an indicator of the positive emotion. Many feature extraction methods have been proposed for detecting a smile in an unconstrained scene. However, most of the existing feature descriptors are too large and not effective to be applied to distinguish smile and non-smile in the real world. In this paper, we proposed an ELM-based smile detection system by using a novel feature extraction method. Motivated by the observation that the mouth shape can effectively reflect a person's smile state, a novel and snappy set of features from a few of facial landmarks around the mouth are extracted. We have tested our algorithms on the smile detection database, and the results indicate that our method is better than the state-of-the-art methods with higher accuracy and lower dimension of features. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:356 / 369
页数:14
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