2020/02/04 by Xianpeng Ji, Yu Ding, Ji, Xianpeng +7 · 4 citations
Computer Science · Engineering · Psychology · #Artificial intelligence #Artificial neural network #Computer Vision and Pattern Recognition (cs.CV) #Computer science #Computer vision #Emotion and Mood Recognition #FOS: Computer and information sciences #FOS: Electrical engineering #Face (sociological concept) #Face recognition and analysis #Feature (linguistics) #Feature extraction #Image (mathematics) #Image and Video Processing (eess.IV) #Pattern recognition (psychology) #Preprocessor #Representation (politics) #Speech and Audio Processing #Texture (cosmology) #cs.CV #eess.IV #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2002.01105
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2020/02/04 · arxiv created 2020/02/08 · arxiv updated 2020/02/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
This paper describes an approach to the facial action units detections. The involved action units (AU) include AU1 (Inner Brow Raiser), AU2 (Outer Brow Raiser), AU4 (Brow Lowerer), AU6 (Cheek Raise), AU12 (Lip Corner Puller), AU15 (Lip Corner Depressor), AU20 (Lip Stretcher), and AU25 (Lip Part). Our work relies on the dataset released by the FG-2020 Competition: Affective Behavior Analysis In-the-Wild (ABAW). The proposed method consists of the data preprocessing, the feature extraction and the AU classification. The data preprocessing includes the detection of face texture and landmarks. The texture static and landmark dynamic features are extracted through neural networks and then fused as the feature latent representation. Finally, the fused feature is taken as the initial hidden state of a recurrent neural network with a trainable lookup AU table. The output of the RNN is the results of AU classification. The detected accuracy is evaluated with 0.5×accuracy + 0.5×F1. Our method achieve 0.56 with the validation data that is specified by the organization committee.