TY - GEN
T1 - Hand gesture interface based on improved adaptive hand area detection and contour signature
AU - Gu, Lei
AU - Yuan, Xiaoyang
AU - Ikenaga, Takeshi
PY - 2012/12/1
Y1 - 2012/12/1
N2 - HMD (head-mounted display) as a promising device is becoming more and more important in daily life. Many companies has been working on it for the next generation human-interface system. This paper presents a real-time hand gesture interface based on TSL (Hue, Saturation, Luminance) adaptive area detection and distance signature with single camera. First, apply self-adaptive skin color detection in TSL color space where skin color data can be clustered to segment hand area. Second, acquire the distance signatures from hand shape contours and obtain possible finger points which reduce the hand gesture recognition problem into finding peaks of one dimensional signature. Last, finger points are labeled by the information of signature. ROC (Receiver Operating Characteristic) Analysis shows the proposed hand area detection method always gives a result in feasible area (TPR>0.91, FPR<0.1) which is suitable for the following contour analysis, indicating that it's more stable and robust compared with other skin color based methods. The evaluation results show the potential of real-time on PC at around 10 fps.
AB - HMD (head-mounted display) as a promising device is becoming more and more important in daily life. Many companies has been working on it for the next generation human-interface system. This paper presents a real-time hand gesture interface based on TSL (Hue, Saturation, Luminance) adaptive area detection and distance signature with single camera. First, apply self-adaptive skin color detection in TSL color space where skin color data can be clustered to segment hand area. Second, acquire the distance signatures from hand shape contours and obtain possible finger points which reduce the hand gesture recognition problem into finding peaks of one dimensional signature. Last, finger points are labeled by the information of signature. ROC (Receiver Operating Characteristic) Analysis shows the proposed hand area detection method always gives a result in feasible area (TPR>0.91, FPR<0.1) which is suitable for the following contour analysis, indicating that it's more stable and robust compared with other skin color based methods. The evaluation results show the potential of real-time on PC at around 10 fps.
KW - adpaptive skin area detection
KW - distance based gesture detection
KW - hand area detection
UR - http://www.scopus.com/inward/record.url?scp=84875675024&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84875675024&partnerID=8YFLogxK
U2 - 10.1109/ISPACS.2012.6473534
DO - 10.1109/ISPACS.2012.6473534
M3 - Conference contribution
AN - SCOPUS:84875675024
SN - 9781467350815
T3 - ISPACS 2012 - IEEE International Symposium on Intelligent Signal Processing and Communications Systems
SP - 463
EP - 468
BT - ISPACS 2012 - IEEE International Symposium on Intelligent Signal Processing and Communications Systems
T2 - 20th IEEE International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2012
Y2 - 4 November 2012 through 7 November 2012
ER -