Facial Emotions Recognition using Gabor Transform and Facial Animation Parameters with Neural Networks

[摘要] The paper proposed an automatic facial emotion recognition algorithm which comprises of two main components: feature extraction and expression recognition. The algorithm uses a Gabor filter bank on fiducial points to find the facial expression features. The resulting magnitudes of Gabor transforms, along with 14 chosen FAPs (Facial Animation Parameters), compose the feature space. There are two stages: the training phase and the recognition phase. Firstly, for the present 6 different emotions, the system classifies all training expressions in 6 different classes (one for each emotion) in the training stage. In the recognition phase, it recognizes the emotion by applying the Gabor bank to a face image, then finds the fiducial points, and then feeds it to the trained neural architecture.

[发布机构] Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani, India^1

[关键词] Different class;Expression recognition;Facial animation parameters;Facial emotions;Facial Expressions;Fiducial points;Gabor transform;Neural architectures