• DocumentCode
    2162074
  • Title

    Embedded neuromorphic vision systems

  • Author

    Irick, Kevin

  • Author_Institution
    SiliconScapes, Pennsylvania State Univ., State College, CA, USA
  • fYear
    2013
  • fDate
    Sept. 29 2013-Oct. 4 2013
  • Firstpage
    1
  • Lastpage
    1
  • Abstract
    The large body of research in perceptual computing has and will continue to enable many intriguing applications such as augmented reality, driver assistance, and personal analytics. Moreover, as wearable first person computing devices become increasingly popular, the demand for highly interactive perceptual computing applications will increase rapidly. Applications including first person assistance and analytics will be pervasive across retail, automotive, and medical domains. However, the computational requirements demanded by future perceptual computing applications will far exceed the capabilities of traditional vision algorithms that are executed on sequential CPUs and GPUs. Hardware accelerators are recognized as key to surpassing the limits of existing sequential architectures. In particular, brain inspired, or neuromorphic, vision accelerators have the potential to support computationally intensive perception algorithms on resource and power constrained devices.
  • Keywords
    computer vision; embedded systems; graphics processing units; image classification; image fusion; interactive systems; neural nets; ubiquitous computing; GPU; augmented reality; automotive domain; bottom-up image saliency; brain inspired sequential; computational requirements; computationally intensive perception algorithm; cortical based object classification; driver assistance; embedded neuromorphic vision systems; first person assistance; hardware accelerator; image data fusion; interactive perceptual computing application; medical domain; neuromorphic vision accelerators; personal analytics; pervasive computing; power constrained devices; resource constrained devices; retail domain; scene GIST extraction; sequential CPU; sequential architecture; vision algorithm; wearable first person computing device; Accuracy; Brain models; Computational modeling; Computer architecture; Machine vision; Neuromorphics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Hardware/Software Codesign and System Synthesis (CODES+ISSS), 2013 International Conference on
  • Conference_Location
    Montreal, QC
  • Type

    conf

  • DOI
    10.1109/CODES-ISSS.2013.6659009
  • Filename
    6659009