From the Publisher:
Face recognition is a task which the human visual system seems to perform almost effortlessly, yet goal of building machines with comparable capabilities has proven difficult to realize. The task requires the ability to locate and track faces through scenes which are often complex and dynamic. Recognition is difficult because of variations in factors such as lighting conditions, viewpoint, body movement and facial expression. Although evidence from psychophysical and neurobiological experiments provides intriguing insights into how we might code and recognize faces, their bearings on computational and engineering solutions are far from clear.
This book describes how to build learning machines to perform face recognition in dynamic scenes. The task at hand is that of engineering robust machine vision systems that can operate under poorly controlled and changing conditions. Many of the issues raised are relevant to object recognition in general, and such visual learning machines have numerous potential applications in areas such as visual surveillance multimedia and visually mediated interaction.
Cited By
Liu S and Wang S An Improved Face Recognition Fusion Algorithm Based on the Features extracted from Gabor, PCA and KPCA Proceedings of the 2nd International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence, (116-121)- Das A, Sengupta A, Ferrer M, Pal U and Blumenstein M Linking face images captured from the optical phenomenon in the wild for forensic science 2017 IEEE International Joint Conference on Biometrics (IJCB), (781-786)
- Wonjun Hwang and Junmo Kim (2015). Markov Network-Based Unified Classifier for Face Recognition, IEEE Transactions on Image Processing, 24:11, (4263-4275), Online publication date: 1-Nov-2015.
- Jain S, Nigam A and Gupta P Age-Invariant face recognition using shape transformation Proceedings of the 9th international conference on Intelligent Computing Theories, (453-461)
- Chakrabarty A, Jain H and Chatterjee A (2013). Volterra kernel based face recognition using artificial bee colonyoptimization, Engineering Applications of Artificial Intelligence, 26:3, (1107-1114), Online publication date: 1-Mar-2013.
- Przybyło J Vision based facial action recognition system for people with disabilities Proceedings of the Third international conference on Information Technologies in Biomedicine, (577-588)
- Passarinho C, Salles E and Sarcinelli-Filho M Detection and tracking faces in unconstrained color video streams Proceedings of the 7th international conference on Advances in visual computing - Volume Part II, (466-475)
- Bouganis C, Park S, Constantinides G and Cheung P (2009). Synthesis and Optimization of 2D Filter Designs for Heterogeneous FPGAs, ACM Transactions on Reconfigurable Technology and Systems, 1:4, (1-28), Online publication date: 1-Jan-2009.
- Lee S, Park K and Kim J (2009). A comparative study of facial appearance modeling methods for active appearance models, Pattern Recognition Letters, 30:14, (1335-1346), Online publication date: 30-Oct-2009.
- Chang C, Tu Y and Chang H Adaptive color space switching based approach for face tracking Proceedings of the 13th international conference on Neural Information Processing - Volume Part II, (244-252)
- Shih F, Fu C and Zhang K (2005). Multi-view face identification and pose estimation using B-spline interpolation, Information Sciences: an International Journal, 169:3-4, (189-204), Online publication date: 1-Feb-2005.
- Hild M and Kuzui R Face recognition based on recursive bayesian fusion of multiple signals and results from expert classifier sets Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication, (239-249)
- Lu J, Plataniotis K and Venetsanopoulos A (2005). Regularization studies of linear discriminant analysis in small sample size scenarios with application to face recognition, Pattern Recognition Letters, 26:2, (181-191), Online publication date: 15-Jan-2005.
- Ruiz-del-Solar J and Vallejos P Motion detection and tracking for an AIBO robot using camera motion compensation and kalman filtering RoboCup 2004, (619-627)
- Jones C and Abbott A (2004). Optimization of color conversion for face recognition, EURASIP Journal on Advances in Signal Processing, 2004, (522-529), Online publication date: 1-Jan-2004.
- Li Y, Gong S and Liddell H (2003). Constructing Facial Identity Surfaces for Recognition, International Journal of Computer Vision, 53:1, (71-92), Online publication date: 1-Jun-2003.
- Zhao W, Chellappa R, Phillips P and Rosenfeld A (2003). Face recognition, ACM Computing Surveys, 35:4, (399-458), Online publication date: 1-Dec-2003.
- De la Torre F and Black M (2003). Robust parameterized component analysis, Computer Vision and Image Understanding, 91:1-2, (53-71), Online publication date: 1-Jul-2003.
- Cho E, Kim D and Lee S Posed face image synthesis using nonlinear manifold learning Proceedings of the 4th international conference on Audio- and video-based biometric person authentication, (946-954)
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