Improved 3D Human Motion Capture Using Kinect Skeleton and Depth Sensor

Abstract

Kinect has been utilized as a cost-effective, easy-to- use motion capture sensor using the Kinect skeleton algorithm. However, a limited number of landmarks and inaccuracies in tracking the landmarks’ positions restrict Kinect’s capability. In order to increase the accuracy of motion capturing using Kinect, joint use of the Kinect skeleton algorithm and Kinect-based marker tracking was applied to track the 3D coordi¬nates of multiple landmarks on human. The motion’s kinematic parameters were calculated using the land¬marks’ positions by applying the joint constraints and inverse kinematics techniques. The accuracy of the proposed method and OptiTrack (NaturalPoint, Inc., USA) was evaluated in capturing the joint angles of a humanoid (as ground truth) in a walking test. In or¬der to evaluate the accuracy of the proposed method in capturing the kinematic parameters of a human, lower body joint angles of five healthy subjects were extracted using a Kinect, and the results were com¬pared to Perception Neuron (Noitom Ltd., China) and OptiTrack data during ten gait trials. The absolute agreement and consistency between each optical sys¬tem and the robot data in the robot test and between each motion capture system and OptiTrack data in the human gait test were determined using intraclass cor¬relations coefficients (ICC3). The reproducibility be¬tween systems was evaluated using Lin’s concordance correlation coefficient (CCC). The correlation coeffi¬cients with 95% confidence intervals (95%CI) were interpreted substantial for both OptiTrack and pro¬posed method (ICC > 0.75 and CCC > 0.95) in hu¬manoid test. The results of the human gait exper¬iments demonstrated the advantage of the proposed method (ICC > 0.75 and RMSE = 1.1460°) over the Kinect skeleton model (ICC < 0.4 and RMSE = 6.5843°).