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
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