Fast GPU implementation of large scale dictionary and sparse representation based vision problems
Arizona State University, Tempe, AZ, USA
IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2010
@conference{nagesh2010fast,
title={Fast GPU implementation of large scale dictionary and sparse representation based vision problems},
author={Nagesh, P. and Gowda, R. and Li, B.},
booktitle={Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on},
pages={1570–1573},
issn={1520-6149},
year={2010},
organization={IEEE}
}
Recently, Computer Vision problems like Face Recognition and Super-Resolution solved using sparse representation based methods with large dictionaries have shown state-of-the-art results. However such methods are computationally prohibitive for typical CPUs, especially for a large dictionary size. We present fast implementation of these methods by exploiting the massively parallel processing capabilities of a GPU within a CUDA framework, owing to its easy off-the-shelf availability and programmer friendliness. We provide details of system level design, memory management and implementation strategies. Further, we integrate the solution to the preferred scientific computational platform – MATLAB.
May 11, 2011 by hgpu
