Gait recognition method based on two-dimension wavelet packet decomposition and complete PCA (Principal Component Analysis)
A technology of wavelet packet decomposition and principal component analysis, which is applied in the field of pattern recognition, can solve the problems of unsimplified feature extraction, large amount of calculation, and low recognition accuracy, and achieve the effects of improving accuracy, good robustness, and reducing calculation consumption
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[0038] figure 1 Proposed for the present invention based on WPD+(2D) 2 Flow chart of PCA's gait recognition algorithm. The whole process includes a training module and a recognition module. The training module is used for training and modeling known and classified gait samples, and generates a classifier that can classify and recognize unknown gait samples. The recognition module is for preprocessing and feature extraction of unknown gait samples, and input the samples to be recognized after feature extraction into the trained classifier to judge the category they belong to and evaluate the recognition effect.
[0039] Provide the explanation of each detailed problem involved in the technical scheme of this invention below in detail:
[0040] Step 1, the preprocessing process is as follows:
[0041] The database we use is a gait database of the Institute of Automation, Chinese Academy of Sciences. This database has separated the background. The work to be done in the presen...
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