Based on the definition of gait parameters， this paper proposes and studies a method of collecting and extracting gait parameters using the Microsoft’s Azure Kinect maker-free motion capture system（hereinafter referred to as Kinect system）. At the same time， adaptive filtering， exponential filtering， Kalman filtering and no filtering conditions are used in data processing to improve the smoothness of gait data. In order to evaluate the accuracy of Kinect system and the effectiveness of filtering， the results of extracted gait parameter are statistically compared with those of the Qualisys marker-based motion capture system （Company of Sweden， hereinafter referred to as Q marker-based） in the synchronous experiment， and the different filtering methods are evaluated accordingly. The results show that， in general， the Kinect system has a high consistency with the Q marker-based， and the results under the three filtering conditions all fall within the 95% consistency limit. In terms of their gait parameters， the results of the gait speed are quite different under all filtering conditions， which cannot be applied. For other parameters， adaptive filtering and Kalman filtering show good consistency. Kinect system can accurately calculate the gait parameters of healthy people by applying the proposed method and smoothing it with Kalman filtering， and it can replace the marker-based device in some cases.