GPU-accelerated computation for robust motion tracking using the CUDA framework Conference Paper uri icon

abstract

  • In this paper, we discuss our implementation of a graphics hardware acceleration of the Vector Coherence Mapping vision processing algorithm. Using this algorithm as our test case, we discuss our optimization strategy for various vision processing operations using NVIDIA's new CUDA programming framework. We also demonstrate how flexibly and readily vision processing algorithms can be mapped onto massively parallelized GPU architecture. Our results and analysis show the GPU implementation exhibits a performance gain of more than 40-fold of speedup over state-of-art CPU implementation of VCM algorithm. 2008 The Institution of Engineering and Technology.

name of conference

  • 5th International Conference on Visual Information Engineering (VIE 2008)

published proceedings

  • 5th International Conference on Visual Information Engineering (VIE 2008)

author list (cited authors)

  • Jing Huang, .., Ponce, S. P., Seung In Park, .., Yong Cao, .., & Quek, F.

citation count

  • 16

complete list of authors

  • Ponce, SP||Quek, F

publication date

  • January 2008