Artificial neural network-based multi-source gait feature extraction and identification method
An artificial neural network and gait feature technology, which is applied in the field of multi-source gait feature extraction and identification, and can solve problems such as unsatisfactory results.
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[0079] A method for gait characterization based on multi-source gait information is proposed, including gait video collected by a camera and human body infrared voltage signal captured by an infrared pyroelectric sensor. Through effective gait feature extraction, multi-source Multi-feature fusion for gait recognition. The key technologies involved include: video processing, infrared pyroelectric signal analysis, image processing, feature extraction, pattern recognition, etc. The technical process is as follows: On the one hand, the moving target in the video image is segmented through target detection on the video sequence, the contour of the moving human body is extracted by using the boundary tracking algorithm, the contour is resampled and normalized, and the skeleton feature parameters are extracted respectively. Transform the peak characteristic parameters with Radon to express the shape information of the human body; on the other hand, perform frequency domain transforma...
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