Parallel Computer Vision

This book addresses an area of perception engineering which deals with constructive processes. A model of the environment is analyzed using the information acquired from mUltiple viewpoints of multiple disparate sensors at multiple time instants. Although the role of successive model building and active exploration of the environment, as is discussed in this book, is of great importance, only a few researchers of machine perception have thus far addressed the problem in these directions. Krotkov's book, which is a modification and continuation of his highly successful dissertation, focuses on active exploratory sensing in the context of spatial layout perception. He uses stereo and focus to obtain distance By information, and to eventually develop cooperative combining techniques. means of a stereo system with verging cameras, it is demonstrated that the distance measurements can be significantly improved by combining two sources. In addition, the problem of merging information from the multiple views is discussed in detail. As the field of perception engineering seems to be of growing scientific and applied importance, both practitioners and researchers in machine perception will find this book a valuable addition to their libraries. RameshJain Series Editor Acknowledgements I would like to thank Professor Ruzena Bajcsy for her constant encouragement and guidance during the five years of research leading to the dissertation upon which this book is based. Without her help in all matters, this work would never have been possible.

This comprehensive book is primarily intended for researchers, computer vision specialists, and high-performance computing specialists who are interested in parallelizing computer vision techniques for the sake of accelerating the run-time of computer vision methods. This book covers different penalization methods on different parallel architectures such as multi-core CPUs and GPUs. It is also a valuable reference resource for researchers at all levels (e.g., undergraduate and postgraduate) who are seeking real-life examples of speeding up the computer vision methods’ run-time.

This book constitutes the refereed proceedings of the 5th International Conference on Computer Vision/Computer Graphics Collaboration Techniques, MIRAGE 2011, held in Rocquencourt, France, in October 2011. The 23 full papers presented were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics with focus on Computer Vision/Computer Graphics Collaboration Techniques involving image analysis/synthesis approaches especially concerning theoretical, computational, experimental or industrial aspects of model-based image analysis and image-based model synthesis.

This book provides comprehensive coverage of methods for the empirical evaluation of computer vision techniques. The practical use of computer vision requires empirical evaluation to ensure that the overall system has a guaranteed performance.The book contains articles that cover the design of experiments for evaluation, range image segmentation, the evaluation of face recognition and diffusion methods, image matching using correlation methods, and the performance of medical image processing algorithms.