Combining Multimodal Features within a Fusion Network for Emotion Recognition in the Wild
Combining Multimodal Features within a Fusion Network for Emotion Recognition in the Wild
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DOI：
10.1145/2818346.2830586
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发表时间：
2015-11
期刊：
影响因子：
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通讯作者：
Bo Sun;Liandong Li;Guoyan Zhou;Xuewen Wu;Jun He;Lejun Yu;Dongxue Li;Qinglan Wei
中科院分区：
文献类型：
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作者：
Bo Sun;Liandong Li;Guoyan Zhou;Xuewen Wu;Jun He;Lejun Yu;Dongxue Li;Qinglan Wei
In this paper, we describe our work in the third Emotion Recognition in the Wild (EmotiW 2015) Challenge. For each video clip, we extract MSDF, LBP-TOP, HOG, LPQ-TOP and acoustic features to recognize the emotions of film characters. For the static facial expression recognition based on video frame, we extract MSDF, DCNN and RCNN features. We train linear SVM classifiers for these kinds of features on the AFEW and SFEW dataset, and we propose a novel fusion network to combine all the extracted features at decision level. The final achievement we gained is 51.02% on the AFEW testing set and 51.08% on the SFEW testing set, which are much better than the baseline recognition rate of 39.33% and 39.13%.
