Machine Vision Beyond Visible Spectrum / edited by Riad Hammoud, Guoliang Fan, Robert W. McMillan, Katsushi Ikeuchi.

Springer eBooks

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.

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

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