Research on Identifying Human Abnormal Gait Features Based on Support Vector Machine
Human abnormal gait feature recognition can analyze the walking posture and pattern of an individual,and deduce the identity information and potential health problems of the human body.Based on this,this paper systematically describes the human abnormal gait feature recognition method based on Support Vector Machine(SVM),analyzes the technical advantages and implementation process of SVM in processing gait data,and carries out test experiments on CASIA-B and OUMVLP datasets,verifying the significant improvement of this method compared with the traditional Back Propagation(BP)neural network in terms of gait recognition accuracy,with a view to providing a new perspective for the study of complex behavior recognition.In order to provide a new perspective for the research of complex behavior recognition.
Support Vector Machine(SVM)human abnormal gaitfeature recognitionmodel construction
万方数据
维普
