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A grand challenge of computer vision is to enable machines to "see people". A solution to this challenge will enable numerous applications in various fields, e.g., security, surveillance, entertainment, human computer interaction, bio-mechanics, etc. This book focuses on two problems in the general area of "looking at people": human pose estimation and human action recognition. The goal of human pose estimation is to identify the body parts of a person from a still image. Human action recognition aims to recognize the actions of a person from a video sequence. We formulate the solutions to these problems as learning structured models. This book is primarily intended for graduate students and researchers in the areas of computer vision, machine learning, probabilistic models, image and video understanding.

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Yang Wang, Ph.D. from Simon Fraser University (Canada), M.Sc. from University of Alberta (Canada), B.Sc. from Harbin Institute of Technology (China). Research interests include computer vision and statistical machine learning.

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