• DocumentCode
    156637
  • Title

    Smart feature detection device for cloud based video recognition system

  • Author

    Ikenaga, Takeshi ; Suzuki, Takumi

  • Author_Institution
    Waseda Univ., Kitakyushu, Japan
  • fYear
    2014
  • fDate
    28-30 April 2014
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Potential of a cloud system combining a smart device and cloud servers is increasing. One of the representative examples is "Siri" which offers a friendly web knowledge navigator based on natural language user interface. Since latest portable devices equip not only a microphone but also a high resolution camera, this kind of cloud based framework is also promising to create various kinds of video based recognition systems. There are two essential components for it: a smart device with a high-resolution camera which is responsible for detecting feature from input video and cloud servers which execute recognition or data search using big data as shown in Fig. 1. This paper describes some key technologies of implementing a smart device for a cloud based recognition system. First, a low complexity SIFT (Scale-invariant feature transform) [1] based key point extraction algorithm and its hardware engine capable of operating at full-HD 60fps video [2] are described. As a technique to reduce network bandwidth, a keypoint of interest (KOI) detection algorithm based on spatio-temporal feature considering mutual dependency and camera motion [3] is also discussed. Finally, some promising application examples are shown.
  • Keywords
    cloud computing; feature extraction; image motion analysis; object detection; object recognition; video signal processing; Big Data; KOI detection algorithm; SIFT based key point extraction algorithm; Siri; Web knowledge navigator; camera motion; cloud based framework; cloud based video recognition system; cloud servers; cloud system; high-resolution camera; keypoint-of-interest; mutual dependency; natural language user interface; scale-invariant feature transform; smart feature detection device; spatio-temporal feature; Approximation algorithms; Cameras; Complexity theory; Computer vision; Feature extraction; Hardware; Histograms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    VLSI Design, Automation and Test (VLSI-DAT), 2014 International Symposium on
  • Conference_Location
    Hsinchu
  • Type

    conf

  • DOI
    10.1109/VLSI-DAT.2014.6834914
  • Filename
    6834914