About this book
This illuminating collection offers a fresh look at the very latest advances in the field of embedded computer vision.
Emerging areas covered by this comprehensive text/reference include the embedded realization of 3D vision technologies for a variety of applications, such as stereo cameras on mobile devices. Recent trends towards the development of small unmanned aerial vehicles (UAVs) with embedded image and video processing algorithms are also examined. The authoritative insights range from historical perspectives to future developments, reviewing embedded implementation, tools, technologies, systems, algorithms, and markets.
Topics and features:
- Presents a series of self-contained articles from an international selection of leading experts in the field
- Discusses in detail three major success stories – the development of the optical mouse, vision for consumer robotics, and vision for automotive safety
- Reviews state-of-the-art research on embedded 3D vision, UAVs, automotive vision, mobile vision apps, and augmented reality
- Examines the potential of embedded computer vision in such cutting-edge areas as the Internet of Things, the mining of large data streams, and in computational sensing
- Describes historical successes, current implementations, and future challenges
This timely volume is essential reading for researchers from academia and industry, practitioners, and innovation managers interested in embedded computer vision. Students of computer vision will also find this to be an inspiring source of information on the field.
Dr. Branislav Kisačanin is the CTO of Embedded Computer Vision at Interphase Corp., Plano, TX, USA. Dr. Margrit Gelautz is an associate professor at Vienna University of Technology, Austria, where she directs the research group on Image and Video Analysis & Synthesis.
Editors and affiliations
- DOI https://doi.org/10.1007/978-3-319-09387-1
- Copyright Information Springer International Publishing Switzerland 2014
- Publisher Name Springer, Cham
- eBook Packages Computer Science
- Print ISBN 978-3-319-09386-4
- Online ISBN 978-3-319-09387-1
- Series Print ISSN 2191-6586
- Series Online ISSN 2191-6594
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