Unconstrained Face Recognition
Unconstrained Face Recognition by Shaohua Kevin Zhou, published by Springer US on November 29, 2010, is a softcover reprint of the hardcover first edition from 2006, comprising 244 pages. This book provides a comprehensive review of face recognition technology, particularly focusing on the challenges and advancements in recognizing human faces under unconstrained conditions. It assembles a collection of novel approaches that enhance recognition performance by leveraging the unique characteristics of these situations, distinguishing it from traditional algorithms.
Readers will find that Unconstrained Face Recognition addresses the complexities of biometric identification, especially in dynamic environments. The content is tailored for a professional audience, including researchers and practitioners in the fields of artificial intelligence, computer vision, and software development. Additionally, advanced-level students in computer science will benefit from the insights and methodologies presented in this volume, which emphasize the importance of adapting recognition techniques to various real-world scenarios.
Official synopsis Publisher
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.
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