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Hessian Interest Points on GPU

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00300862" target="_blank" >RIV/68407700:21230/16:00300862 - isvavai.cz</a>

  • Result on the web

    <a href="http://vision.fe.uni-lj.si/cvww2016/proceedings/papers/08.pdf" target="_blank" >http://vision.fe.uni-lj.si/cvww2016/proceedings/papers/08.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Hessian Interest Points on GPU

  • Original language description

    This paper is about interest point detection and GPU programming. We take a popular GPGPU implementation of SIFT - the de-facto standard in fast interest point detectors - SiftGPU and implement modifications that according to recent research result in better performance in terms of repeatability of the detected points. The interest points found at local extrema of the Difference of Gaussians (DoG) function in the original SIFT are replaced by the local extrema of determinant of Hessian matrix of the intensity function. Experimentally we show that the GPU implementation of Hessian-based detector (i) surpasses in repeatability the original DoG-based implementation, (ii) gives result very close to those of a reference CPU implementation, and (iii) is significantly faster than the CPU implementation. We show what speedup is achieved for different image sizes and provide analysis of computational cost of individual steps of the algorithm. The source code is publicly available.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JD - Use of computers, robotics and its application

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    N - Vyzkumna aktivita podporovana z neverejnych zdroju

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 21st Computer Vision Winter Workshop

  • ISBN

    978-961-90901-7-6

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

  • Publisher name

    Slovenian Pattern Recognition Society

  • Place of publication

    Ljubljana

  • Event location

    Rimske Toplice

  • Event date

    Feb 3, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article