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• Preface. Part I: Active Vision: V. Cantoni, G. Caputo, and L. Lombardi, Attentional Engagement in Vision Systems. Y. Yeshurun, Attentional Mechanisms in Computer Vision. M. Savini, The Active Vision Idea. E. Trucco, Active Model Acquisition and Sensor Planning. A. Verri, The Regularization of Early Vision. Part II: Integrating Visual Modules: M. Bertolotto, E. Bruzzone, and L. DeFloriani, Geometric Modeling and Spatial Reasoning.V. Roberto, Vision as Uncertain Knowledge. V. Di Gesu and D. Tegolo, Distributed Systems for Fusion of Visual Infomation. E. Ardizzone, A. Chella, and S. Gaglio, Hybrid Computation and Reasoning for Artificial Vision. Part III: VisualCommunication: A.M. Iacono, Illusion and Difference. S. Levialdi, P. Mussio, N. Bianchi, and P. Bottoni, Computing with/on Images. A. Del Bimbo, Visual Databases. S-K. Chang, Visual Languages for Tele-Action Objects. Subject Index.
• (source: Nielsen Book Data)

Artificial Vision is a rapidly growing discipline, aiming to build computational models of the visual functionalities in humans, as well as machines that emulate them. Visual communication in itself involves a numberof challenging topics with a dramatic impact on contemporary culture where human-computer interaction and human dialogue play a more and more significant role. This state-of-the-art book brings together carefully selected review articles from world renowned researchers at the forefront of this exciting area. The contributions cover topics including image processing, computational geometry, optics, pattern recognition, and computer science. The book is divided into three sections. Part I covers active vision; Part II deals with the integration of visual with cognitive capabilities; and Part III concerns visual communication. Artificial Vision will be essential reading for students and researchers in image processing, vision, and computer science who want to grasp the current concepts and future directions of this challenging field.
(source: Nielsen Book Data)

• Preface. Part I: Active Vision: V. Cantoni, G. Caputo, and L. Lombardi, Attentional Engagement in Vision Systems. Y. Yeshurun, Attentional Mechanisms in Computer Vision. M. Savini, The Active Vision Idea. E. Trucco, Active Model Acquisition and Sensor Planning. A. Verri, The Regularization of Early Vision. Part II: Integrating Visual Modules: M. Bertolotto, E. Bruzzone, and L. DeFloriani, Geometric Modeling and Spatial Reasoning.V. Roberto, Vision as Uncertain Knowledge. V. Di Gesu and D. Tegolo, Distributed Systems for Fusion of Visual Infomation. E. Ardizzone, A. Chella, and S. Gaglio, Hybrid Computation and Reasoning for Artificial Vision. Part III: VisualCommunication: A.M. Iacono, Illusion and Difference. S. Levialdi, P. Mussio, N. Bianchi, and P. Bottoni, Computing with/on Images. A. Del Bimbo, Visual Databases. S-K. Chang, Visual Languages for Tele-Action Objects. Subject Index.
• (source: Nielsen Book Data)

Artificial Vision is a rapidly growing discipline, aiming to build computational models of the visual functionalities in humans, as well as machines that emulate them. Visual communication in itself involves a numberof challenging topics with a dramatic impact on contemporary culture where human-computer interaction and human dialogue play a more and more significant role. This state-of-the-art book brings together carefully selected review articles from world renowned researchers at the forefront of this exciting area. The contributions cover topics including image processing, computational geometry, optics, pattern recognition, and computer science. The book is divided into three sections. Part I covers active vision; Part II deals with the integration of visual with cognitive capabilities; and Part III concerns visual communication. Artificial Vision will be essential reading for students and researchers in image processing, vision, and computer science who want to grasp the current concepts and future directions of this challenging field.
(source: Nielsen Book Data)

• Function spaces vs. Scaling Functions: Tools for Image Classification. Stéphane Jaffard, Patrice Abry and Stéphane Roux
• A Second Order Model for 3D-texture Extraction. Maïtine Bergounioux and Minh Phuong Tran
• Analysis of Texture Anisotropy Through Extended Fractional Brownian Fields. Hermine Biermé and Frédéric J.P. Richard
• Image Reconstruction via Hypoelliptic Diffusion on the Bundle of Directions of the Plane. Ugo Boscain, Jean Duplaix, Jean-Paul Gauthier, Francesco Rossi
• Projective Invariant Features Detection and the Registration group. Françoise Dibos
• Morphological Component Analysis for Decomposing Dynamic Textures. Sloven Dubois, Renaud Péteri and Michel Ménard
• Texture Enhancing Based on Variational Image Decomposition. F. Frühauf, C. Pontow, O. Scherzer
• A Locally Anisotropic Model for Image Texture Extraction. Loïc Piffet
• A Neural Field Model for Motion Estimation. Émilien Tlapale, Pierre Kornprobst, Guillaume Masson and Olivier Faugeras
• Non-Local Regularization and Registration of Multi-Valued Images by PDE's and VariationalMethods on Higher Dimensional Spaces. David Tschumperlé and Luc Brun.

The contributions appearing in this volume are a snapshot of the different topics that were discussed during the conference. They mainly concern, image reconstruction, texture extraction and image classification and involve a variety of different methods and applications. Therefore it was impossible to split the papers into generic groups which is why they are presented in alphabetic order. However they mainly concern : texture analysis (5 papers) with different techniques (variational analysis, wavelet and morphological component analysis, fractional Brownian fields), geometrical methods (2 papers) for restoration and invariant feature detection, classification (with multifractal analysis), neurosciences imaging and analysis of Multi-Valued Images.

• Preface to the Second Edition; Preface to the First Edition; Contents; 1 Introduction; 2 Fundamental Principles of Holography; 2.1 Light Waves; 2.2 Interference; 2.3 ; 2.3.1 General; 2.3.2 ; 2.3.3 Spatial Coherence; 2.4 ; 2.5 Speckle; 2.6 ; 2.6.1 Hologram Recording and Reconstruction; 2.6.2 The ; 2.7 ; 2.7.1 Generation of Holographic Interferograms; 2.7.2 Displacement Measurement by HI; 2.7.3 Holographic ; 2.7.4 Measurement by HI; 2.7.5 Phase Shifting HI; 2.7.6 ; 3 Digital Holography; 3.1 General Principles; 3.2 ; 3.2.1 Reconstruction by the ; 3.2.2 Reconstruction by the ; 3.2.3.

• 3.3 Shift and Suppression of DC-Term and Conjugate Image3.3.1 of the DC Term; 3.3.2 Tilted Reference Wave; 3.3.3 ; 3.4 Recording of Digital Holograms; 3.4.1 Image Sensors; 3.4.2 Spatial Frequency Requirements; 3.4.3 Cameras for Digital Hologram Recording; 3.4.4 Recording Set-ups; 3.4.5 Stability Requirements; 3.4.6 Light Sources; 4 Digital Holographic Interferometry (DHI); 4.1 General Principles; 4.2 Deformation Measurement; 4.2.1 Quantitative Displacement Measurement; 4.2.2 Mechanical Materials Properties; 4.2.3 Thermal Materials Properties; 4.2.4 Non-destructive Testing; 4.3.

• 4.3.1 Two-Illumination-Point Method4.3.2 Two- and Multi-wavelength Method; 4.3.3 Hierarchical Phase Unwrapping; 4.4 Measurement of Refractive Index Variations; 5 Digital Holographic Particle Sizing and Microscopy; 5.1 Introduction; 5.2 Recording and Replay Conditions; 5.2.1 In-line Recording; 5.2.2 Off-axis Recording; 5.2.3 Image Resolution; 5.2.4 Holographic Depth-of-Field and Depth-of-Focus; 5.2.5 Optical ; 5.3 Data Processing and Autofocusing of Holographic Images; 5.4 Some Applications in Imaging and Particle Sizing; 5.4.1 Particle Sizing; 5.4.2 (DHM); 5.4.3 Holographic Tomography.

• 5.4.4 Phase Shifting DHM5.4.5 Particle Image Velocimetry (PIV); 5.4.6 Underwater Digital Holography; 6 Special Techniques; 6.1 Applications Using Short Light; 6.1.1 Light-in-Flight Measurements; 6.1.2 Short-Coherence ; 6.2 ; 6.3 of Digital Holograms; 6.4 ; 6.4.1 Fundamentals of Comparative Holography; 6.4.2 Comparative Digital Holography; 6.5 Encrypting of Information with Digital Holography; 6.6 Synthetic ; 6.7 Holographic Pinhole Camera; 7 Computational Wavefield Sensing; 7.1 Overview; 7.2 Phase Retrieval; 7.2.1 Projection Based Methods; 7.2.2 Gradient Search Methods.

• 7.2.3 Deterministic Methods7.3 Shear Interferometry for Wavefield Sensing; 7.3.1 Wavefront Reconstruction; 7.3.2 Computational Shear Interferometry; 7.4 Shack-Hartmann Wavefront Sensing; 8 Speckle Metrology; 8.1 Electronic Speckle Pattern Interferometry (ESPI); 8.2 Digital Shearography; 8.3 Digital Speckle Photography; 8.4 Comparison of Conventional HI, ESPI and Digital HI; Appendix AThe Fourier Transform; Appendix BPhase Transformation of a Spherical Lens; Appendix CSimple Reconstruction Routines; References; Index.

This highly practical and self-contained guidebook explains the principles and major applications of digital hologram recording and numerical reconstruction (Digital Holography). A special chapter is designated to digital holographic interferometry with applications in deformation and shape measurement and refractive index determination. Applications in imaging and microscopy are also described. Spcial techniques such as digital light-in-flight holography, holographic endoscopy, information encrypting, comparative holography, and related techniques of speckle metrology are also treated.

• 1. Target Recognition in Infrared: Local Feature Based Person Detection and Tracking Beyond the Visible Spectrum.- Fuzzy mixture of Gaussians for the detection of moving objects in and beyond visible spectrum.- Dynamic Appearance Learning by Adaptive Kalman Filters for Robust Infrared Tracking.- Pedestrian Association and Localization in Monocular FIR Video Sequence.- Vehicle Matching and Recognition under Large Variations of Pose and Illumination.-
• 2. Multi-Sensor Fusion and Smart Sensors: Fusion of a Camera and a Laser Range Sensor for Vehicle Recognition.- Geometric Sequence (GS) Imaging with Bayesian Smoothing for Optical and Capacitive Imaging Sensors.- A System Approach to Adaptive Multimodal Sensor Designs.
• -3. Hyperspectral Image Analysis: Statistical Affine Invariant Hyperspectral Texture Descriptors Based Upon Harmonic Analysis.- Face Tracking and Classification Using Hyperspectral Video Sequences.- On near real-time moving Object Detection and Tracking in Multi-spectral Aerial imagery.
• (source: Nielsen Book Data)

The material of this book encompasses many disciplines, including visible, infrared, far infrared, millimeter wave, microwave, radar, synthetic aperture radar, and electro-optical sensors as well as the very dynamic topics of image processing, computer vision and pattern recognition. This book is composed of six parts: * Advanced background modeling for surveillance * Advances in Tracking in Infrared imagery * Methods for Pose estimation in Ultrasound and LWIR imagery * Recognition in multi-spectral and synthetic aperture radar * Fusion of disparate sensors * Smart Sensors.
(source: Nielsen Book Data)