Embedded Computer Vision

Mathias Kölsch, Steven Butner (auth.), Branislav Kisačanin PhD, Shuvra S. Bhattacharyya PhD, Sek Chai PhD (eds.)184800303X, 978-1-84800-303-3, 978-1-84800-304-0, 1848003048

Embedded Computer Vision, exemplified by the migration from powerful workstations to embedded processors in computer vision applications, is a new and emerging 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 academic 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 emerging field of embedded computer vision. Supplementary material can be found at http://www.embeddedvisioncentral.com.

Table of contents :
Front Matter….Pages I-XXVIII
Front Matter….Pages 1-1
Hardware Considerations for Embedded Vision Systems….Pages 3-26
Design Methodology for Embedded Computer Vision Systems….Pages 27-47
We Canwatch It For You Wholesale….Pages 49-76
Front Matter….Pages 77-77
Using Robust Local Features on DSP-Based Embedded Systems….Pages 79-100
Benchmarks of Low-Level Vision Algorithms for DSP, FPGA, and Mobile PC Processors….Pages 101-120
SAD-Based Stereo Matching Using FPGAs….Pages 121-138
Motion History Histograms for Human Action Recognition….Pages 139-162
Embedded Real-Time Surveillance Using Multimodal Mean Background Modeling….Pages 163-175
Implementation Considerations for Automotive Vision Systems on a Fixed-Point DSP….Pages 177-194
Towards OpenVL: Improving Real-Time Performance of Computer Vision Applications….Pages 195-216
Front Matter….Pages 217-217
Mobile Challenges for Embedded Computer Vision….Pages 219-235
Challenges in Video Analytics….Pages 237-256
Challenges of Embedded Computer Vision in Automotive Safety Systems….Pages 257-279
Back Matter….Pages 281-282