TY - GEN
T1 - Fast PCA-based face recognition on GPUs
AU - Woo, Youngsang
AU - Yi, Cheongyong
AU - Yi, Youngmin
PY - 2013/10/18
Y1 - 2013/10/18
N2 - Face recognition is very important in many applications including surveillance, biometrics, and other domains. Fast face recognition is required if she wants to train or test more images or to increase the resolution of an input image for better accuracy in the recognition. Meanwhile, Graphics Processing Units (GPUs) have become widely available, offering the opportunity for real-time face recognition even for larger set of images with a high resolution. In this paper, we explore the design space of parallelizing a PCA (Principal Component Analysis) based face recognition algorithm and propose a fast face recognizer on GPUs by exploiting the fine-grained data-parallelism found in the face recognition algorithm. We successfully accelerated the major three tasks by 120-folds, 70-folds, and 110-folds, compared to a sequential C implementation. For the end-to-end comparison, our CUDA face recognizer achieved a 30-fold speedup.
AB - Face recognition is very important in many applications including surveillance, biometrics, and other domains. Fast face recognition is required if she wants to train or test more images or to increase the resolution of an input image for better accuracy in the recognition. Meanwhile, Graphics Processing Units (GPUs) have become widely available, offering the opportunity for real-time face recognition even for larger set of images with a high resolution. In this paper, we explore the design space of parallelizing a PCA (Principal Component Analysis) based face recognition algorithm and propose a fast face recognizer on GPUs by exploiting the fine-grained data-parallelism found in the face recognition algorithm. We successfully accelerated the major three tasks by 120-folds, 70-folds, and 110-folds, compared to a sequential C implementation. For the end-to-end comparison, our CUDA face recognizer achieved a 30-fold speedup.
KW - CUDA
KW - Face recognition
KW - GPU
KW - PCA
UR - http://www.scopus.com/inward/record.url?scp=84890458503&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2013.6638138
DO - 10.1109/ICASSP.2013.6638138
M3 - Conference contribution
AN - SCOPUS:84890458503
SN - 9781479903566
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 2659
EP - 2663
BT - 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
T2 - 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Y2 - 26 May 2013 through 31 May 2013
ER -