Micro-expression recognition based on differential energy maps and CGBP

作者：Yu Ming; Wang Yingzi; Yu Yang; Liu Yi

来源：Journal of Southwest Jiaotong University, 2016, 51(6): 1222-1229.

DOI：10.3969/j.issn.0258-2724.2016.06.024

• Binary patterns
• Difference energy image
• Differential energy
• Extreme learning machine
• Facial Expressions
• Micro-expressions
• State of the art
• Temporal textures

Micro-expression is a kind of facial expression which is autonomous and cannot be disguised. It has a close relation with credibility. Moreover, it has only a short duration and hard to be recognized. A micro-expression recognition algorithm based on the differential energy maps and centralized Gabor binary patterns (CGBP) was presented. Firstly, this algorithm uses the difference among micro-expression sequence images to calculate the energy maps and obtain the phase changes of facial muscle. Secondly, CGBP operators that combines Gabor and centralized binary patterns was proposed to extract micro-expression features. Finally, ELM classifier was used to classify micro-expressions. Experimental results on CASME micro-expression database show that compared with the state-of-the-art LBP-TOP, DTSA3, Gabor, VLBP, and CBP-TOP algorithms, this proposed method can obtain better spatial and temporal texture features and achieve higher recognition rate, which reaches 86.54% averagely.

• 出版日期2016
• 单位河北工业大学