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Biologically-Inspired Computer Vision: Fundamentals and Applications Hardcover – 7 Oct 2015
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From the Back Cover
This book serves as a comprehensive but rigorous reference in the area of biologically inspired computer vision modeling. Biologically inspired vision, that is the study of visual systems of living beings, can be considered as a two–way process. On the one hand, living organisms can provide a source of inspiration for
new computationally efficient and robust vision models, and on the other hand, machine vision approaches can provide new insights into understanding biological visual systems. Over the different chapters, this book covers a wide range from the fundamental to the more specialized topics. It also analyzes the influence of these studies in the design of novel, more advanced vision sensors. In particular, the last section of the book provides an overview of a few representative applications and current state of the art of the research in this area. This book contains 18 chapters that have been organized in four different parts: Fundamentals Sensing Modeling Applications.
About the Author
Prof. Gabriel Cristobal is currently a Research Scientist at the Instituto de Optica, Spanish Council for Scientific Research (CSIC). His current research interests are joint representations, vision modelling and multidimensional signal processing. Prof. Cristobal is a Senior Member of the IEEE, member of the Optical Society of America (OSA), EURASIP Spanish liaison officer for the period 2009–2010 and member of the ISO/IEC JTC1/SC29/WG1 (JPEG2000). He is co–editor of the book "Optical and Digital Image Processing" by G. Cristobal, P. Schelkens and H. Thienpont, Wiley VCH, 2011.
Prof. Matthias Keil is currently Ramon and Cajal researcher in the Basic Psychology Department of the University of Barcelona (Spain). He received his PhD degree from the University of Ulm (Germany) for proposing a novel architecture for early visual information processing in the human brain. His research interests are centered on computational neuroscience and diffusion–based image processing. Examples of former and current research lines include computational modeling of brightness and lightness perception, tone mapping, time to contact perception, modeling of insect vision, and biologically motivated collision avoidance systems.
Dr. Laurent Perrinet is researcher in Computational Neuroscience at the "Institut de Neurosciences de la Timone" at Aix–Marseille Université, France. His research is focused on bridging the complex dynamics of realistic models of large–scale models of spiking neurons with functional models of low–level vision.
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