Face Detection and Recognition

Asit Kumar Datta is a former professor of the University of Calcutta (CU), Kolkata, India, where he served in the Department of Applied Physics and the Department of Applied Optics and Photonics. He holds an M.Tech and Ph.D from the same university. Dr. Datta spent 19 years as a professor and a total of 40 years of teaching and research at the post-graduate level at CU. In addition, he served for 8 years as a principal scientist/principal scientific officer of a CU research center in optical electronics. Widely published in international journals and conference proceedings, Dr. Datta has guided 14 scholars toward their Ph.Ds and has published nearly 125 papers. He has contributed significantly in the areas of photonic computation, photonic and electronic instrumentation, optical communications, and pattern recognition. He represented India at the International Commission on Optics and the International Commission on Illumination. Madhura Datta is the assistant director of the University Grants Commission-Human Resources Development Center, University of Calcutta, Kolkata, India. She holds an M.Sc in computer and information science, and an M.Tech and Ph.D in computer science and engineering from the University of Calcutta. Her primary areas of research are face detection and recognition. Her work has been featured in various technical publications and conference proceedings, including the Journal of Pattern Recognition Research, Computer Vision and Image Understanding, International Journal of Pattern Recognition and Artificial Intelligence, International Conference on Pattern Recognition and Machine Intelligence, and IEEE International Conference on Intelligent Human Computer Interaction. Pradipta Kumar Banerjee is an associate professor in the Department of Electrical Engineering of the Future Institute of Engineering and Management, Kolkata, India. He holds a B.Sc, B.Tech, M.Tech, and Ph.D from the

Introduction. Face detection and recognition techniques. Subspace based face recognition. Face detection by Bayesian approach. Face detection in colour and infrared images. Intelligent face detection. Real time face detection. Face space boundary selection for face detection and recognition. Evolutionary design for face recognition. Frequency domain correlation filters in face recognition. Subspace based face recognition in frequency domain. Landmark localization for face recognition. Two dimensional synthetic face generation using set estimation technique. Datasets of face images and performance tests for face recognition.