TY - GEN
T1 - Hybrid gesture recognition system for short-range use
AU - Minagawa, Akihiro
AU - Fan, Wei
AU - Katsuyama, Yutaka
AU - Takebe, Hiroaki
AU - Ozawa, Noriaki
AU - Hotta, Yoshinobu
AU - Sun, Jun
PY - 2012
Y1 - 2012
N2 - In recent years, various gesture recognition systems have been studied for use in television and video games[1]. In such systems, motion areas ranging from 1 to 3 meters deep have been evaluated[2]. However, with the burgeoning popularity of small mobile displays, gesture recognition systems capable of operating at much shorter ranges have become necessary. The problems related to such systems are exacerbated by the fact that the camera's field of view is unknown to the user during operation, which imposes several restrictions on his/her actions. To overcome the restrictions generated from such mobile camera devices, and to create a more flexible gesture recognition interface, we propose a hybrid hand gesture system, in which two types of gesture recognition modules are prepared and with which the most appropriate recognition module is selected by a dedicated switching module. The two recognition modules of this system are shape analysis using a boosting approach (detection-based approach)[3] and motion analysis using image frame differences (motion-based approach)(for example, see[4]). We evaluated this system using sample users and classified the resulting errors into three categories: errors that depend on the recognition module, errors caused by incorrect module identification, and errors resulting from user actions. In this paper, we show the results of our investigations and explain the problems related to short-range gesture recognition systems.
AB - In recent years, various gesture recognition systems have been studied for use in television and video games[1]. In such systems, motion areas ranging from 1 to 3 meters deep have been evaluated[2]. However, with the burgeoning popularity of small mobile displays, gesture recognition systems capable of operating at much shorter ranges have become necessary. The problems related to such systems are exacerbated by the fact that the camera's field of view is unknown to the user during operation, which imposes several restrictions on his/her actions. To overcome the restrictions generated from such mobile camera devices, and to create a more flexible gesture recognition interface, we propose a hybrid hand gesture system, in which two types of gesture recognition modules are prepared and with which the most appropriate recognition module is selected by a dedicated switching module. The two recognition modules of this system are shape analysis using a boosting approach (detection-based approach)[3] and motion analysis using image frame differences (motion-based approach)(for example, see[4]). We evaluated this system using sample users and classified the resulting errors into three categories: errors that depend on the recognition module, errors caused by incorrect module identification, and errors resulting from user actions. In this paper, we show the results of our investigations and explain the problems related to short-range gesture recognition systems.
KW - Gesture recognition
KW - detection based gesture recognition
KW - hybrid approach
KW - motion based gesture detection
KW - short-range gesture recognition
UR - http://www.scopus.com/inward/record.url?scp=84863157861&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863157861&partnerID=8YFLogxK
U2 - 10.1117/12.906953
DO - 10.1117/12.906953
M3 - Conference contribution
AN - SCOPUS:84863157861
SN - 9780819489425
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Proceedings of SPIE-IS and T Electronic Imaging - Image Processing
T2 - Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II
Y2 - 23 January 2012 through 25 January 2012
ER -