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Embedded Computer Vision

  • Branislav Kisačanin
  • Shuvra S. Bhattacharyya
  • Sek Chai

Part of the Advances in Pattern Recognition book series (ACVPR)

Table of contents

  1. Front Matter
    Pages I-XXVIII
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Mathias Kölsch, Steven Butner
      Pages 3-26
    3. Sankalita Saha, Shuvra S. Bhattacharyya
      Pages 27-47
    4. Alan J. Lipton
      Pages 49-76
  3. Advances in Embedded Computer Vision

    1. Front Matter
      Pages 77-77
    2. Clemens Arth, Christian Leistner, Horst Bischof
      Pages 79-100
    3. Daniel Baumgartner, Peter Roessler, Wilfried Kubinger, Christian Zinner, Kristian Ambrosch
      Pages 101-120
    4. Kristian Ambrosch, Martin Humenberger, Wilfried Kubinger, Andreas Steininger
      Pages 121-138
    5. Hongying Meng, Nick Pears, Michael Freeman, Chris Bailey
      Pages 139-162
    6. Senyo Apewokin, Brian Valentine, Dana Forsthoefel, Linda Wills, Scott Wills, Antonio Gentile
      Pages 163-175
    7. Changsong Shen, James J. Little, Sidney Fels
      Pages 195-216
  4. Looking Ahead

    1. Front Matter
      Pages 217-217
    2. Nikhil Gagvani
      Pages 237-256
    3. Yan Zhang, Arnab S. Dhua, Stephen J. Kiselewich, William A. Bauson
      Pages 257-279
  5. Back Matter
    Pages 281-282

About this book

Introduction

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.

Keywords

Automotive Safety Computer Vision Driver Assistance Embedded Computer Vision Embedded Systems Pattern Recognition Video Analytics Video Surveillance action recognition human action recognition

Editors and affiliations

  • Branislav Kisačanin
    • 1
  • Shuvra S. Bhattacharyya
    • 2
  • Sek Chai
    • 3
  1. 1.Texas InstrumentsDallasUSA
  2. 2.University of MarylandCollege ParkUSA
  3. 3.MotorolaSchaumburgUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-84800-304-0
  • Copyright Information Springer-Verlag London Limited 2009
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-84800-303-3
  • Online ISBN 978-1-84800-304-0
  • Buy this book on publisher's site