Face recognition has been actively studied over the past decade and continues to be a big research challenge. Just recently, researchers have begun to investigate face recognition under unconstrained conditions. Unconstrained Face Recognition provides a comprehensive review of this biometric, especially face recognition from video, assembling a collection of novel approaches that are able to recognize human faces under various unconstrained situations. The underlying basis of these approaches is that, unlike conventional face recognition algorithms, they exploit the inherent characteristics of the unconstrained situation and thus improve the recognition performance when compared with conventional algorithms.
Unconstrained Face Recognition is structured to meet the needs of a professional audience of researchers and practitioners in industry. This volume is also suitable for advanced-level students in computer science.
表中的内容
Fundamentals, Preliminaries and Reviews.- Fundamentals.- Preliminaries and Reviews.- Face Recognition Under Variations.- Symmetric Shape from Shading.- Generalized Photometric Stereo.- Illuminating Light Field.- Facial Aging.- Face Recognition Via Kernel Learning.- Probabilistic Distances in Reproducing Kernel Hilbert Space.- Matrix-Based Kernel Subspace Analysis.- Face Tracking and Recognition from Videos.- Adaptive Visual Tracking.- Simultaneous Tracking and Recognition.- Probabilistic Identity Characterization.- Summary and Future Research Directions.- Summary and Future Research Directions.
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