The problem of face recognition has been studied widely in the past two decades. Even though considerable progress has been made, e.g. in achieving better recognition rates, handling difficult environmental conditions etc., there has not been any widespread implementation of this technology. Most probably, the reason lies in not giving adequate consideration to practical problems such as communication costs and computational overhead. The book addresses the practical face recognition problem � e.g. a scenario that may arise in client recognition in Automated Teller Machines or employee authentication in large offices. Such scenarios can not be handled by traditional machine learning methods. This book will develop novel methods to solve this problem from a completely new perspective. It proposes employing random projections for dimensionality reduction. Such dimensionality reduction demands new classification methods which is the main interest of this book.

About the Author

Angshul completed his Masters in Applied Science in Electrical and Computer Engineering from the University of British Columbia, Canada in 2009. He specialized in Signal Processing and Pattern Recognition. Angshul did his Bachelors in Electronics and Telecommunication Engineering from Bengal Engineering and Science University, India.

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