共查询到1条相似文献,搜索用时 0 毫秒
1.
A model-based hand gesture recognition system 总被引:2,自引:0,他引:2
This paper introduces a model-based hand gesture recognition system, which consists of three phases: feature extraction,
training, and recognition. In the feature extraction phase, a hybrid technique combines the spatial (edge) and the temporal
(motion) information of each frame to extract the feature images. Then, in the training phase, we use the principal component
analysis (PCA) to characterize spatial shape variations and the hidden Markov models (HMM) to describe the temporal shape
variations. A modified Hausdorff distance measurement is also applied to measure the similarity between the feature images
and the pre-stored PCA models. The similarity measures are referred to as the possible observations for each frame. Finally,
in recognition phase, with the pre-trained PCA models and HMM, we can generate the observation patterns from the input sequences,
and then apply the Viterbi algorithm to identify the gesture. In the experiments, we prove that our method can recognize 18
different continuous gestures effectively.
Received: 19 May 1999 / Accepted: 4 September 2000 相似文献