Dec

01

2022

Embedded Computer Vision By Branislav Kisacanin

Laser 1 Dec 2022 08:47 LEARNING » e-book

Embedded Computer Vision By Branislav Kisacanin
English | PDF | 2009 | 300 Pages | ISBN : 184800303X | 10.51 MB

Embedded Computer Vision, exemplified by the migration from powerful workstations to embedded processors in computer vision applications, is a new and emeg field that enables an associated shift in application development and implementation.


This comprehensive volume brings together a wealth of experiences from leading researchers in the field of embedded computer vision, from both acad and industrial research centers, and covers a broad range of challenges and trade-offs brought about by this paradigm shift. Part I provides an exposition of basic issues and applications in the area necessary for understanding the present and future work. Part II offers chapters based on the most recent research and results. Finally, the last part looks ahead, providing a sense of what major applications could be expected in the near future, describing challenges in mobile environments, video analytics, and automotive safety applications.

Features

Discusses the latest state-of-the-art techniques in embedded computer vision

Presents a thorough introductory section on hardware and architectures, design methodologies, and video analytics to aid the reader's understanding through the following chapters

Offers emphasis on tackling important problems for society, safety, security, health, mobility, connectivity, and energy efficiency

Discusses evaluation of trade-offs required to design cost-effective systems for successful products

Explores the advantages of various architectures, development of high-level software frameworks and cost-effective algorithmic alternatives

Examines issues of implementation on fixed-point processors, presented through an example of an automotive safety application

Offers insights from leaders in the field on what future applications will be

This book is a welcome collection of stand-alone articles, ideal for researchers, practitioners, and graduate students. It provides historical perspective, the latest research results, and a vision for future developments in the emeg field of embedded computer vision. Supplementary material can be found at



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