• شماره ركورد كنفرانس
    3297
  • عنوان مقاله

    Quick SIFT(QSIFT), An Approach to Reduce SIFT Computational Cost

  • عنوان به زبان ديگر
    Quick SIFT(QSIFT), An Approach to Reduce SIFT Computational Cost
  • پديدآورندگان

    Fazel Zahra Shiraz University Iran - shiraz , Famouri Mahmoud Shiraz University Iran - shiraz , Nazemi Azadeh Shiraz University Iran - shiraz , Azimifar Zohreh Shiraz University Iran - shiraz

  • كليدواژه
    Real-time application , Natural image statistics , Feature matching , Feature extraction , Feature descriptor , Feature detector , Interest points
  • سال انتشار
    آبان 1396
  • عنوان كنفرانس
    نوزدهمين سمپوزيوم بين المللي هوش مصنوعي و پردازش سيگنال
  • چكيده لاتين
    SIFT has been proven to be the most robust local rotation and illumination invariant feature descriptor. Being fully scale invariant is the most important advantage of this descriptor. The major drawback of SIFT is time complexity which prevents utilizing SIFT in real-time applications. This paper describes a method to increase the speed of SIFT feature extraction using keypoint estimation and approximation instead of keypoint calculation in various scales. This research attempts to decrease SIFT computational cost without sacrificing performance and propose quick SIFT method (QSIFT). The recent researches in this area have approved that direct feature value computation is more expensive than the value extrapolation. Consequently, the contribution of this research is to reduces the time execution without losing accuracy.
  • كشور
    ايران
  • تعداد صفحه 2
    4
  • از صفحه
    1
  • تا صفحه
    4