Biologically Inspired Computer Vision
A Wiley VCH book, edited by G. Cristóbal, L. Perrinet and M. Keil
As the state-of-the-art imaging technologies became more and more advanced, yielding scientific data at unprecedented detail and volume, the need to process and interpret all the data has made image processing and computer vision also increasingly important. Sources of data that have to be routinely dealt with today applications include video transmission, wireless communication, automatic fingerprint processing, massive databases, non-weary and accurate automatic airport screening, robust night vision to name a few. Multidisciplinary inputs from other disciplines such as computational neuroscience, cognitive science, mathematics, physics and biology will have a fundamental impact in the progress of imaging and vision sciences. One of the advantages of the study of biological organisms is to devise very different type of computational paradigms beyond the usual von Neumann e.g. by implementing a neural network with a high degree of local connectivity. This is a comprehensive and rigorous reference in the area of biologically motivated vision sensors. The study of biologically visual systems can be considered as a two way avenue. On the one hand, biological organisms can provide a source of inspiration for new computational efficient and robust vision models and on the other hand machine vision approaches can provide new insights for understanding biological visual systems. Along the different chapters, this book covers a wide range of topics from fundamental to more specialized topics, including visual analysis based on a computational level, hardware implementation, and the design of new more advanced vision sensors. The last two sections of the book provide an overview of a few representative applications and current state of the art of the research in this area. This makes it a valuable book for graduate, Master, PhD students and also researchers in the field.
Published: October 07, 2015
Table of contents
This book contains 18 chapters that have been organized in four different parts: Fundamentals – Sensing – Modeling – Applications.
- Front Matter (pages i–xxii)
Part I: Fundamentals
Chapter 1: Introduction (pages 1–10), Gabriel Cristóbal, Laurent U. Perrinet and Matthias S. Keil
- Chapter 2: Bioinspired Vision Sensing (pages 11–28), Christoph Posch
Chapter 3: Retinal Processing: From Biology to Models and Applications (pages 29–52), David Alleysson and Nathalie Guyader
Chapter 5: Perceptual Psychophysics (pages 81–108), C. Alejandro Parraga
Part II: Sensing
- Chapter 6: Bioinspired Optical Imaging (pages 109–142), Mukul Sarkar
- Chapter 7: Biomimetic Vision Systems (pages 143–174), Reinhard Voelkel
Chapter 8: Plenoptic Cameras (pages 175–200), Fernando Pérez Nava, Alejandro Pérez Nava, Manuel Rodríguez Valido and Eduardo Magdaleno Castellò
Part III: Modelling
Chapter 9: Probabilistic Inference and Bayesian Priors in Visual Perception (pages 201–220), Grigorios Sotiropoulos and Peggy Seriès
Chapter 10: From Neuronal Models to Neuronal Dynamics and Image Processing (pages 221–244), Matthias S. Keil
Chapter 11: Computational Models of Visual Attention and Applications (pages 245–266), Olivier Le Meur and Matei Mancas
Chapter 12: Visual Motion Processing and Human Tracking Behavior (pages 267–294), Anna Montagnini, Laurent U. Perrinet and Guillaume S. Masson
Chapter 13: Cortical Networks of Visual Recognition (pages 295–318), Christian Thériault, Nicolas Thome and Matthieu Cord
Chapter 14: Sparse Models for Computer Vision (pages 319–346), Laurent U. Perrinet
Chapter 15: Biologically Inspired Keypoints (pages 347–374), Alexandre Alahi, Georges Goetz and Emmanuel D'Angelo
Part IV: Applications
- Chapter 16: Nightvision Based on a Biological Model (pages 375–404), Magnus Oskarsson, Henrik Malm and Eric Warrant
- Chapter 17: Bioinspired Motion Detection Based on an FPGA Platform (pages 405–424), Tim Köhler
Chapter 18: Visual Navigation in a Cluttered World (pages 425–446), N. Andrew Browning and Florian Raudies:
the book on the web
- . Biologically Inspired Computer Vision, URL . Wiley-VCH Verlag GmbH \& Co. KGaA, Weinheim, Germany, 2015.
All material (c) L. Perrinet. Please check the copyright notice.