Group-level emotion recognition based on faces, scenes, skeletons features

Dejian Li; Ruiming Luo; Shouqian Sun

doi:10.1117/12.2557175

3 January 2020 Group-level emotion recognition based on faces, scenes, skeletons features

Dejian Li, Ruiming Luo, Shouqian Sun

Proceedings Volume 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019); 1137307 (2020) https://doi.org/10.1117/12.2557175
Event: Eleventh International Conference on Graphics and Image Processing, 2019, Hangzhou, China

Abstract

In this paper, we propose a deep neural network based approach for the group-level emotion recognition in 6th Emotion Recognition in the Wild Challenge (EmotiW 2018). The task of this challenge is to classify a group’s perceived emotion as Positive, Neutral or Negative. Like the most of current researchers on visual emotion recognition, we mainly focus on facial, scene and body clues in images. We treat each clue as mono-model feature and apply early fusion method to combine them together. Experimental results show that our proposed method has outperformed the baseline techniques with the overall test accuracy of 62.90%.

Citation Download Citation

Dejian Li, Ruiming Luo, and Shouqian Sun "Group-level emotion recognition based on faces, scenes, skeletons features", Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 1137307 (3 January 2020); https://doi.org/10.1117/12.2557175

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