A Novel Approach for Facial Expression Recognition Using Euclidean Distances
Annu1, Chander Kant2
1Annu, M. Tech Student, DCSA, KUK, kurukshetra, have Published two more Papers Except this Paper.
2Dr. Chander Kant Verma, Assistant professor, DCSA, KUK, Kurukshetra. P.hd. of Biometrics from DCSA, KUK. He is Editor Chief in IJITKM, Associate Editor in IJCSC and in IJEE. He is also Member of Editorial Board in IJCA, IJSC, IJISP and IJCIRP.
Manuscript received on May 12, 2013. | Revised Manuscript received on June 13, 2013. | Manuscript published on June 30, 2013. | PP: 94-97 | Volume-2, Issue-5, June 2013. | Retrieval Number: E1712062513/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: There has been a growing interest in automatic face and facial expression recognition from facial images due to a variety of potential applications in law enforcement, security control, and human computer interaction. However, despite of all the advances in automatic facial expression recognition, it still remains a challenging problem. This paper describes an idea of recognizing the human face even in the presence of strong facial expressions using the Eigen face method. The features extracted from the face image sequences can be efficiently used for face and facial expression recognition. Firstly, we compute the Eigen value and Eigen vectors of the input image and then finally the input facial image was recognized when similarity was obtained by calculating the minimum Euclidean distance between the input image and the different expressions.
Keywords: Eigen face, Eigen value, Euclidean distance, Facial expression recognition, Facial features, Face recognition.