2011/04/07 by Soumen Bag, Bag, Soumen, Soumen Barik +5
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Face and Expression Recognition #Face recognition and analysis #cs.CV
paper · pdf · doi:10.48550/arxiv.1104.1237
7 pages, 2 figures. In proceedings of the Second International Conference on Information Processing (ICIP), pp. 198-204, Bangalore, India, 2008
arxiv created 2011/04/07 · openalex publication_date 2011/04/07 · arxiv updated 2011/04/08 · openalex created_date 2022/08/30 · openalex updated_date 2026/07/28
Facial expressions convey non-verbal cues, which play an important role in interpersonal relations. Automatic recognition of human face based on facial expression can be an important component of natural human-machine interface. It may also be used in behavioural science. Although human can recognize the face practically without any effort, but reliable face recognition by machine is a challenge. This paper presents a new approach for recognizing the face of a person considering the expressions of the same human face at different instances of time. This methodology is developed combining Eigenface method for feature extraction and modified k-Means clustering for identification of the human face. This method endowed the face recognition without using the conventional distance measure classifiers. Simulation results show that proposed face recognition using perception of k-Means clustering is useful for face images with different facial expressions.