ACTIVE APPEARANCE BASED POSE AND ILLUMINATION VARIANT FACE RECOGNITION FROM VIDEO SEQUENCES

Anupkumar Awaradi, Deepak Kumar

Abstract: Surveillance video provides security by monitoring the people entering and leaving the premises. Face recognition in video may act as a tool to record the information with minimal manual intervention. The major difficulty is that the faces are captured in different pose and illumination in the video. The recognition of these faces from the video sequences is complex. In this paper, we have addressed the face recognition problem in different pose and illumination.We have created a set of ten video sequences for ten people with different pose and illumination and extracted the faces at different angles and illumination from these video sequences to create a face database. Active Appearance Model (AAM) is used to create a feature vector for each face that exists in the database. Artificial Neural Network (ANN) is trained to recognize the face from the appearance feature vectors. The proposed method reduces the computational complexity involved in recognizing the faces in different pose and illumination. We have achieved a recognition rate of 96.1% on the test set of the face database.

Keywords: Face Recognition; Active Appearance Model; Neural Network; Video Sequences;

DOI: https://doi.org/10.15623/ijret.2015.0426013