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Computer Vision in the Infrared Spectrum - Challenges and Approaches (Paperback)
Loot Price: R1,554
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Computer Vision in the Infrared Spectrum - Challenges and Approaches (Paperback)
Series: Synthesis Lectures on Computer Vision
Expected to ship within 10 - 15 working days
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Human visual perception is limited to the visual-optical spectrum.
Machine vision is not. Cameras sensitive to the different infrared
spectra can enhance the abilities of autonomous systems and
visually perceive the environment in a holistic way. Relevant scene
content can be made visible especially in situations, where sensors
of other modalities face issues like a visual-optical camera that
needs a source of illumination. As a consequence, not only human
mistakes can be avoided by increasing the level of automation, but
also machine-induced errors can be reduced that, for example, could
make a self-driving car crash into a pedestrian under difficult
illumination conditions. Furthermore, multi-spectral sensor systems
with infrared imagery as one modality are a rich source of
information and can provably increase the robustness of many
autonomous systems. Applications that can benefit from utilizing
infrared imagery range from robotics to automotive and from
biometrics to surveillance. In this book, we provide a brief yet
concise introduction to the current state-of-the-art of computer
vision and machine learning in the infrared spectrum. Based on
various popular computer vision tasks such as image enhancement,
object detection, or object tracking, we first motivate each task
starting from established literature in the visual-optical
spectrum. Then, we discuss the differences between processing
images and videos in the visual-optical spectrum and the various
infrared spectra. An overview of the current literature is provided
together with an outlook for each task. Furthermore, available and
annotated public datasets and common evaluation methods and metrics
are presented. In a separate chapter, popular applications that can
greatly benefit from the use of infrared imagery as a data source
are presented and discussed. Among them are automatic target
recognition, video surveillance, or biometrics including face
recognition. Finally, we conclude with recommendations for
well-fitting sensor setups and data processing algorithms for
certain computer vision tasks. We address this book to prospective
researchers and engineers new to the field but also to anyone who
wants to get introduced to the challenges and the approaches of
computer vision using infrared images or videos. Readers will be
able to start their work directly after reading the book supported
by a highly comprehensive backlog of recent and relevant literature
as well as related infrared datasets including existing evaluation
frameworks. Together with consistently decreasing costs for
infrared cameras, new fields of application appear and make
computer vision in the infrared spectrum a great opportunity to
face nowadays scientific and engineering challenges.
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