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Mobile Challenges for Embedded Computer Vision

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Embedded Computer Vision

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

Abstract

The mobile environment poses uniquely challenging constraints for designers of embedded computer vision systems. There are traditional issues such as size, weight, and power, which are readily evident. However, there are also other less tangible obstacles related to technology acceptance and business models that stand in the way of a successful product deployment. In this chapter, I describe these issues as well as other qualities desired in a mobile smart camera using computer vision algorithms to “see and understand” the scene. The target platform of discussion is the mobile handset, as this platform is poised to be the ubiquitous consumer device all around the world.

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Author information

Authors and Affiliations

  1. Motorola Labs, Schaumburg, IL, USA

    Sek Chai

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  1. Sek Chai
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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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© 2009 Springer-Verlag London Limited

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Chai, S. (2009). Mobile Challenges for Embedded Computer Vision. 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_11

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  • DOI: https://doi.org/10.1007/978-1-84800-304-0_11

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84800-303-3

  • Online ISBN: 978-1-84800-304-0

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