DocumentCode :
3742582
Title :
A robust and parallel-friendly distance image based hand detection
Author :
Zhaohua Yi;Xiaoqi Hu;Byunghyun Jang;Kyung Ki Kim
Author_Institution :
The University of Mississippi, Department of Computer and Information Science, 201 Weir Hall, University, MS, 38677
fYear :
2015
Firstpage :
33
Lastpage :
34
Abstract :
Hand detection plays an important role in Human Computer Interaction (HCI). Most of the existing hand detection methods rely on the contour shape of hand after skin color segmentation. Such contour shape based approaches, however, are easily distorted by noises and other skin color segments. In this paper, we present a distance image based approach using CPU-GPU heterogeneous computing. Our experiments demonstrate that our proposed distance image based hand detection is robust and fast, reaching up to 97.32% palm detection rate where 80.36% of cases have more than 3 fingers detected on commodity processors. We also achieved 5.0 times speed-up for 320×240 images, and 17.5 times for 640×480 images.
Keywords :
"Thumb","Skin","Image color analysis","Colored noise","Image segmentation","Robustness"
Publisher :
ieee
Conference_Titel :
SoC Design Conference (ISOCC), 2015 International
Type :
conf
DOI :
10.1109/ISOCC.2015.7401651
Filename :
7401651
Link To Document :
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