International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 4 Issue 9, September 2015


Real Time Control System Based on Hand Gesture Detection and Recognition

Shalini [92] | Dr. Rekha Patil [4]


Abstract: Hand gesture recognition techniques have been studied for more than two decades. Several solutions have been developed, however, little attention has been paid on the human factors, e. g. the intuitiveness of the applied hand gestures. This study was inspired by the movie Minority Report, in which a gesture-based interface was presented to a large audience. In the movie, a video-browsing application was controlled by hand gestures. Nowadays the tracking of hand movements and the computer recognition of gestures is realizable, however, for a usable system it is essential to have an intuitive set of gestures. The system functions used in Minority Report were reverse engineered and a user study was conducted, in which participants were asked to express these functions by means of hand gestures. We were interested how people formulate gestures and whether we could find any pattern in these gestures. In particular, we focused on the types of gestures in order to study intuitiveness, and on the kinetic features to discover how they influence computer recognition. We found that there are typical gestures for each function, and these are not necessarily related to the technology people are used to. This result suggests that an intuitive set of gestures can be designed, which is not only usable in this specific application, but can be generalized for other purposes as well. Furthermore, directions are given for computer recognition of gestures regarding the number of hands used and the dimensions of the space where the gestures are formulated.


Keywords: Hand gesture recognition, Local binary pattern LBP, K nearest neighbour algorithm KNN, Eigen classifier


Edition: Volume 4 Issue 9, September 2015,


Pages: 743 - 749


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