Augmented Vision Perception in Infrared

This book covers theoretical and experimental work in sub-areas of machine perception and is structured into 4 parts.The first part presents novel methodologies to extract unique thermal infrared signatures to uniquely represent targets in multi-spectral and infrared scenes. The second part tackles problems related to rapid gain change in thermal imagery, background estimation, detection of pedestrians, robust multimodal image registration and object segmentation, and finally automatic detection of low-resolution moving objects. Part three addresses face and facial expression recognition in low-light environments. The last part focuses on Multi-Sensory and Multi-Modal Target Tracking.This practical reference offers researchers, students and software engineers a thorough understanding of how core low-level building blocks of a machine perception system are implemented. Readers will find in-depth coverage of recent state-of-the-art perception algorithms and experiments.