Computer Vision and Image Understanding
| Hi-index | 0.00 |
Spurred by security and safety challenges, research efforts in thermographic sensors have advanced greatly, resulting in better performance in remote surveillance, object recognition, guidance and so on. This comprehensive survey provides a thorough account of the recent deployment of infrared sensors in modern applications of computer vision, as well as in-depth descriptions of the worlds best machine vision algorithms and intelligent analytics. The book will help readers understand the motivations, activities, trends and directions of researchers and engineers in the machine-perception field, and offers them a view of the future in this rapidly evolving area. Features: Offers an up-to-date and in-depth coverage of theoretical and experimental work in sub-areas of machine perception in infrared, thermal, hyperspectral, intensified and laser imagery Highlights new trends and directions in the field of applied machine vision *beyond* the visible spectrum Covers applications including homeland security, public transportation, surveillance, medical and military Emphasizes the merging of machine perception applications and non-visual imaging in intensified, near infrared, thermal infrared, laser, polarimetric and hyperspectral bands Presents advanced techniques for identifying unique infrared signatures and classifying small-resolution objects above and under the soil Focuses on describing successful non-contact, thermal video analysis methodologies to compute vital-signs measurements on the human face, neck and breast Deals with automatic moving-object detection in airborne, low-resolution near-infrared and thermal videos Illustrates fusion and registration techniques of multiple disparate multi-channel visible and thermal sensors for accurate image segmentation Discusses multi-target tracking using laser and infrared sensors, as well as augmented human-computer interaction using infrared eye tracking. Provides a critical analysis of state-of-the-art techniques in the field of computer vision, including comparison of existing methods and benchmarking This practical and broad-ranging text offers researchers, advanced students and software engineers alike a thorough understanding of the theory and experimental field-operational characteristics of key algorithmic building blocks of computer vision systems, using non-visual infrared imagery. It contains enough material for a two-semester upper-division or advanced graduate course on topics related to machine vision and its applications. Dr Riad Ibrahim Hammoud is a Senior Research Scientist at Delphi Electronics & Safety and also the successful Springer author of the following books: Passive Eye Monitoring, Face Biometrics for Personal Identification, and Interactive Video.