Throughout much of machine vision's early years the infrared
imagery has suffered from return on investment despite its
advantages over visual counterparts. Recently, the ?scal momentum
has switched in favor of both manufacturers and practitioners of
infrared technology as a result of today's rising security and
safety challenges and advances in thermographic sensors and their
continuous drop in costs. This yielded a great impetus in achieving
ever better performance in remote surveillance, object recognition,
guidance, noncontact medical measurements, and more. The purpose of
this book is to draw attention to recent successful efforts made on
merging computer vision applications (nonmilitary only) and
nonvisual imagery, as well as to ?ll in the need in the literature
for an up-to-date convenient reference on machine vision and
infrared technologies. Augmented Perception in Infrared provides a
comprehensive review of recent deployment of infrared sensors in
modern applications of computer vision, along with in-depth
description of the world's best machine vision algorithms and
intel- gent analytics. Its topics encompass many disciplines of
machine vision, including remote sensing, automatic target
detection and recognition, background modeling and image
segmentation, object tracking, face and facial expression
recognition, - variant shape characterization, disparate sensors
fusion, noncontact physiological measurements, night vision, and
target classi?cation. Its application scope includes homeland
security, public transportation, surveillance, medical, and
military. Mo- over, this book emphasizes the merging of the
aforementioned machine perception applications and nonvisual
imaging in intensi?ed, near infrared, thermal infrared, laser,
polarimetric, and hyperspectral bands.
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