Statistical Methods and Models for Video-Based Tracking, Modeling, and Recognition (Foundations and Trends (R) in Signal Processing) (Foundations and Trends® in Signal Processing) - Softcover
Synopsis
Computer vision systems attempt to understand a scene and its components from mostly visual information. The geometry exhibited by the real world, the influence of material properties on scattering of incident light, and the process of imaging introduce constraints and properties that are key to solving some of these tasks. In the presence of noisy observations and other uncertainties, the algorithms make use of statistical methods for robust inference. Statistical Methods and Models for Video-based Tracking, Modeling, and Recognition highlights the role of geometric constraints in statistical estimation methods, and how the interplay of geometry and statistics leads to the choice and design of algorithms. In particular, it illustrates the role of imaging, illumination, and motion constraints in classical vision problems such as tracking, structure from motion, metrology, activity analysis and recognition, and appropriate statistical methods used in each of these problems.
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About the Author
Rama Chellappa is Minta Martin Professor of Engineering and an affiliate Professor of Computer Science at University of Maryland, College Park. He is also affiliated with the Center for Automation Research and UMIACS, and is serving as the Chair of the ECE department. He is a recipient of the K. S. Fu Prize from the IAPR and the Society, Technical Achievement and Meritorious Service Awards from the IEEE Signal Processing Society. He also received the Technical Achievement and Meritorious Service Awards from the IEEE Computer Society. In 2010, he was recognized as an Outstanding ECE by Purdue University. He is a Fellow of the IEEE, IAPR, OSA and AAAS, a Golden Core Member of the IEEE Computer Society, and has served as a Distinguished Lecturer of the IEEE Signal Processing Society as well as the President of the IEEE Biometrics Council.
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