Bøker i Advances in Computer Vision and Pattern Recognition-serien

Practical in approach, this book describes a range of common imaging techniques, reconstruction techniques and image artifacts, reviews image enhancement methods, discusses image transfer and archiving, and includes exercises and a glossary of abbreviations.

examines the effective features that characterize static hand poses and introduces a unified framework to enforce both temporal and spatial constraints for hand parsing; proposes a new classifier architecture for real-time hand pose recognition and a novel hand segmentation and gesture recognition system.

This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED). illustrates how the quadratic assignment problem of GED can be reduced to a linear sum assignment problem;

Unlike other computer vision textbooks, this guide takes a unique approach in which the initial focus is on practical application and the procedures necessary to actually build a computer vision system.

Tensor signal processing is an emerging field with important applications to computer vision and image processing. This book presents the state of the art in this new branch of signal processing, offering a great deal of research and discussions by leading experts in the area.

This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model.