Perceived behavioral factors, including single-joint movements and configure different joints. Therefore suggests a new location-based differences in the characteristics of the type of joint, the joint including a static posture, movement, displacement including behavioral information for identification. Differences in the use of the joint region both time and space explicitly configured to simulate individual joints kinetics and different joints. Then principal component analysis (PCA) to obtain the desired characteristics. At the same time a simple nonparametric Bayesian nearest neighbor (NBNN) classifier to classify many types of behavior. This avoids the frame NBNN classification descriptors to quantify computing " image to the category" distance rather than distance " image to the image" of. Data 15-20 is sufficient to achieve the gesture and action recognition, without application of the entire video sequence, which greatly reduces the latency and improve the ef

HellokinectMAT\HellokinectMAT\App.config
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HellokinectMAT

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