Implementation and Optimization of Image Processing Algorithms on Embedded GPU

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著者

    • SINGHAL Nitin
    • the Digital Media & Communication R&D Center, Samsung Electronics Co. Ltd.
    • TOO Jin Woo
    • the School of Information and Communication Engineering, Inha University
    • CHOI Ho Yeol
    • the School of Information and Communication Engineering, Inha University
    • PARK In Kyu
    • the School of Information and Communication Engineering, Inha University

抄録

In this paper, we analyze the key factors underlying the implementation, evaluation, and optimization of image processing and computer vision algorithms on embedded GPU using OpenGL ES 2.0 shader model. First, we present the characteristics of the embedded GPU and its inherent advantage when compared to embedded CPU. Additionally, we propose techniques to achieve increased performance with optimized shader design. To show the effectiveness of the proposed techniques, we employ cartoon-style non-photorealistic rendering (NPR), speeded-up robust feature (SURF) detection, and stereo matching as our example algorithms. Performance is evaluated in terms of the execution time and speed-up achieved in comparison with the implementation on embedded CPU.

収録刊行物

  • IEICE transactions on information and systems

    IEICE transactions on information and systems 95(5), 1475-1484, 2012-05-01

    The Institute of Electronics, Information and Communication Engineers

参考文献:  18件中 1-18件 を表示

各種コード

  • NII論文ID(NAID)
    10030943232
  • NII書誌ID(NCID)
    AA10826272
  • 本文言語コード
    ENG
  • 資料種別
    ART
  • ISSN
    09168532
  • データ提供元
    CJP書誌  J-STAGE 
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