Advanced Institute of Convergence Information Technology
Vision based band gesture recognition provides a more nature and powerful means for human-computer interaction. A fast detection process of hand gesture and an effective feature extraction process are presented. The proposed a hand gesture
recognition algorithm comprises four main steps. First use Camshift algorithm to track skin color after closing process. Second,in order to extract feature, we use BEA to extract the boundary of the hand. Third, the benefits of Fourier descriptor are invariance to the starting point of the boundary, deformation, and rotation, and therefore transform the starting point of the boundary by Fourier transformation. Finally, outline feature for the nonlinear non-separable type of data was classified by using SVM. Experimental results showed the accuracy is 93.4% in average and demonstrated the feasibility of proposed system.
Information Science and Digital Content Technology (ICIDT), 2012 8th International Conference on, pp.490-494