Title :
Bias analyses of spontaneous facial expression database
Author :
Zhaoyu Wang ; Shangfei Wang ; Yachen Zhu ; Qiang Ji
Author_Institution :
Key Lab. of Comput. & Communicating Software of Anhui Province Sch. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China
Abstract :
In this paper, cross-corpora evaluations are used to analyze the bias of spontaneous facial expression databases. Local binary pattern, Gabor, eigenface and fisherface features are extracted and applied to the four spontaneous expression databases: USTC-NVIE, VAM, Belfast Naturalistic and SEMAINE to recognize arousal (high/low) and valance (positive/negative) respectively. Experimental results indicate that there exists bias among different spontaneous expression databases. The emotion-induction methods, the variety of subjects and the quantity of raters may have caused such a bias.
Keywords :
Gabor filters; feature extraction; visual databases; Belfast Naturalistic; Gabor feature extraction; SEMAINE; USTC-NVIE; VAM; arousal recognition; bias analysis; cross-corpora evaluations; eigenface feature extraction; emotion-induction methods; fisherface feature extraction; local binary pattern; rater quantity; spontaneous facial expression database; subject variety; valance recognition; Databases; Face recognition; Feature extraction; Principal component analysis; Training; Videos;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4
