Details

Autor(en) / Beteiligte

• Cristóbal, Gabriel,
• Perrinet, Laurent,
• Keil, Matthias S.,
• Alahi, Alexandre,

Titel

Biologically inspired computer vision : fundamentals and applications

Auflage

1st ed

Ort / Verlag

Weinheim, Germany : Wiley-VCH Verlag GmbH & Co. KGaA,

Erscheinungsjahr

2016

Link zum Volltext

• Wiley Online Library - AutoHoldings Books

Beschreibungen/Notizen

• Description based upon print version of record.
• Includes bibliographical references at the end of each chapters and index.
• Intro -- Related Titles -- Title Page -- Copyright -- Table of Contents -- List of Contributors -- Foreword -- Part I: Fundamentals -- Chapter 1: Introduction -- 1.1 Why Should We Be Inspired by Biology? -- 1.2 Organization of Chapters in the Book -- 1.3 Conclusion -- Acknowledgments -- References -- Chapter 2: Bioinspired Vision Sensing -- 2.1 Introduction -- 2.2 Fundamentals and Motivation: Bioinspired Artificial Vision -- 2.3 From Biological Models to Practical Vision Devices -- 2.4 Conclusions and Outlook -- References -- Chapter 3: Retinal Processing: From Biology to Models and Applications -- 3.1 Introduction -- 3.2 Anatomy and Physiology of the Retina -- 3.3 Models of Vision -- 3.4 Application to Digital Photography -- 3.5 Conclusion -- References -- Chapter 4: Modeling Natural Image Statistics -- 4.1 Introduction -- 4.2 Why Model Natural Images? -- 4.3 Natural Image Models -- 4.4 Computer Vision Applications -- 4.5 Biological Adaptations to Natural Images -- 4.6 Conclusions -- References -- Chapter 5: Perceptual Psychophysics -- 5.1 Introduction -- 5.2 Laboratory Methods -- 5.3 Psychophysical Threshold Measurement -- 5.4 Classic Psychophysics: Theory and Methods -- 5.5 Signal Detection Theory -- 5.6 Psychophysical Scaling Methods -- 5.7 Conclusions -- References -- Part II: Sensing -- Chapter 6: Bioinspired Optical Imaging -- 6.1 Visual Perception -- 6.2 Polarization Vision - Object Differentiation/Recognition -- 6.3 High-Speed Motion Detection -- 6.4 Conclusion -- References -- Chapter 7: Biomimetic Vision Systems -- 7.1 Introduction -- 7.2 Scaling Laws in Optics -- 7.3 The Evolution of Vision Systems -- 7.4 Manufacturing of Optics for Miniaturized Vision Systems -- 7.5 Examples for Biomimetic Compound Vision Systems -- References -- Chapter 8: Plenoptic Cameras -- 8.1 Introduction.
• 8.2 Light Field Representation of the Plenoptic Function -- 8.3 The Plenoptic Camera -- 8.4 Applications of the Plenoptic Camera -- 8.5 Generalizations of the Plenoptic Camera -- 8.6 High-Performance Computing with Plenoptic Cameras -- 8.7 Conclusions -- References -- Part III: Modelling -- Chapter 9: Probabilistic Inference and Bayesian Priors in Visual Perception -- 9.1 Introduction -- 9.2 Perception as Bayesian Inference -- 9.3 Perceptual Priors -- 9.4 Outstanding Questions -- References -- Chapter 10: From Neuronal Models to Neuronal Dynamics and Image Processing -- 10.1 Introduction -- 10.2 The Membrane Equation as a Neuron Model -- 10.3 Application 1: A Dynamical Retinal Model -- 10.4 Application 2: Texture Segregation -- 10.5 Application 3: Detection of Collision Threats -- 10.6 Conclusions -- Acknowledgments -- References -- Chapter 11: Computational Models of Visual Attention and Applications -- 11.1 Introduction -- 11.2 Models of Visual Attention -- 11.3 A Closer Look at Cognitive Models -- 11.4 Applications -- 11.5 Conclusion -- References -- Chapter 12: Visual Motion Processing and Human Tracking Behavior -- 12.1 Introduction -- 12.2 Pursuit Initiation: Facing Uncertainties -- 12.3 Predicting Future and On-Going Target Motion -- 12.4 Dynamic Integration of Retinal and Extra-Retinal Motion Information: Computational Models -- 12.5 Reacting, Inferring, Predicting: A Neural Workspace -- 12.6 Conclusion -- Acknowledgments -- References -- Chapter 13: Cortical Networks of Visual Recognition -- 13.1 Introduction -- 13.2 Global Organization of the Visual Cortex -- 13.3 Local Operations: Receptive Fields -- 13.4 Local Operations in V1 -- 13.5 Multilayer Models -- 13.6 A Basic Introductory Model -- 13.7 Idealized Mathematical Model of V1: Fiber Bundle -- 13.8 Horizontal Connections and the Association Field.
• 13.9 Feedback and Attentional Mechanisms -- 13.10 Temporal Considerations, Transformations and Invariance -- 13.11 Conclusion -- References -- Chapter 14: Sparse Models for Computer Vision -- 14.1 Motivation -- 14.2 What Is Sparseness? Application to Image Patches -- 14.3 SparseLets: A Multiscale, Sparse, Biologically Inspired Representation of Natural Images -- 14.4 SparseEdges: Introducing Prior Information -- 14.5 Conclusion -- Acknowledgments -- References -- Chapter 15: Biologically Inspired Keypoints -- 15.1 Introduction -- 15.2 Definitions -- 15.3 What Does the Frond-End of the Visual System Tell Us? -- 15.4 Bioplausible Keypoint Extraction -- 15.5 Biologically Inspired Keypoint Representation -- 15.6 Qualitative Analysis: Visualizing Keypoint Information -- 15.7 Conclusions -- References -- Part IV: Applications -- Chapter 16: Nightvision Based on a Biological Model -- 16.1 Introduction -- 16.2 Why Is Vision Difficult in Dim Light? -- 16.3 Why Is Digital Imaging Difficult in Dim Light? -- 16.4 Solving the Problem of Imaging in Dim Light -- 16.5 Implementation and Evaluation of the Night-Vision Algorithm -- 16.6 Conclusions -- Acknowledgment -- References -- Chapter 17: Bioinspired Motion Detection Based on an FPGA Platform -- 17.1 Introduction -- 17.2 A Motion Detection Module for Robotics and Biology -- 17.3 Insect Motion Detection Models -- 17.4 Overview of Robotic Implementations of Bioinspired Motion Detection -- 17.5 An FPGA-Based Implementation -- 17.6 Experimental Results -- 17.7 Discussion -- 17.8 Conclusion -- Acknowledgments -- References -- Chapter 18: Visual Navigation in a Cluttered World -- 18.1 Introduction -- 18.2 Cues from Optic Flow: Visually Guided Navigation -- 18.3 Estimation of Self-Motion: Knowing Where You Are Going -- 18.4 Object Detection: Understanding What Is in Your Way.
• 18.5 Estimation of TTC: Time Constraints from the Expansion Rate -- 18.6 Steering Control: The Importance of Representation -- 18.7 Conclusions -- Acknowledgments -- References -- Index -- End User License Agreement.
• English
• Description based on online resource; title from PDF title page (ebrary, viewed November 5, 2015).