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Design Methodology for Embedded Computer Vision Systems

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Book cover Embedded Computer Vision

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

Computer vision has emerged as one of the most popular domains of embedded applications. The applications in this domain are characterized by complex, intensive computations along with very large memory requirements. Parallelization and multiprocessor implementations have become increasingly important for this domain, and various powerful new embedded platforms to support these applications have emerged in recent years. However, the problem of efficient design methodology for optimized implementation of such systems remains vastly unexplored. In this chapter, we look into the main research problems faced in this area and how they vary from other embedded design methodologies in light of key application characteristics in the embedded computer vision domain.We also provide discussion on emerging solutions to these various problems.

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Authors and Affiliations

  1. RIACS/NASA Ames Research Center, Moffett Field, CA, USA

    Sankalita Saha

  2. University of Maryland, College Park, MD, USA

    Shuvra S. Bhattacharyya

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  1. Sankalita Saha
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  2. Shuvra S. Bhattacharyya
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Editors and Affiliations

  1. Texas Instruments, Dallas, TX, USA

    Branislav Kisačanin PhD

  2. University of Maryland, College Park, MD, USA

    Shuvra S. Bhattacharyya PhD

  3. Motorola, Schaumburg, IL, USA

    Sek Chai PhD

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Saha, S., Bhattacharyya, S.S. (2009). Design Methodology for Embedded Computer Vision Systems. In: Kisačanin, B., Bhattacharyya, S.S., Chai, S. (eds) Embedded Computer Vision. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84800-304-0_2

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  • DOI: https://doi.org/10.1007/978-1-84800-304-0_2

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