期刊论文

Chen, Jingying

英文

Optik

0030-4026

2019

182

647-657

10.1016/j.ijleo.2019.01.020

National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61702208]; National Key R&D Program of China [2017YFB1401300, 2017YFB1401303]; Natural Science Foundation of Hubei ProvinceNatural Science Foundation of Hubei Province [2017CFB504, 2018CFB404]; Research Funds of CCNU from the Colleges Basic Research and Operation of MOE [CCNU17QN0003, CCNU17ZDJC04]

本校为第一且通讯机构

Detecting spontaneous smile in unconstrained environment is a challenging problem mainly due to the large intra-class variations caused by head poses. This paper presents a real-time smile detection method based on conditional random regression forests. Since the relation between image patches and smile intensity is modelled conditional to head pose, the proposed smile detection method is not sensitive to head poses. To achieve high smile detection performance, techniques including regression forest, multiple-label dataset augmentation and non-informative patch removement are employed. Experim...