Measurement of body joint angles from two Kinect image sequences based on mean shift tracking

• Main Authors: Yung-Chin Chen, 陳永秩
• Other Authors: Hsi-Jian Lee
• Format: Others
• Language: en_US
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/81986788078952786299

碩士 === 慈濟大學 === 醫學資訊學系碩士班 === 103 === Range of motion (ROM) is commonly used to assess a patient’s joint function in physical therapy. Because motion capture systems are generally very expensive, physical therapists mostly use simple rulers to measure patients’ joint angles in clinical diagnosis, which will suffer from low accuracy, low reliability, and subjective. In this study we used color and depth image feature from two sets of low-cost Microsoft Kinect to reconstruct 3D joint positions, and then calculate moveable joint angles to assess the ROM. A Gaussian background model is first used to segment the human body from the depth images. The 3D coordinates of the joints are reconstructed from both color and depth images. To track the location of joints throughout the sequence more precisely, we adopt the mean shift algorithm to find out the center of voxels upon the joints. The joint moveable angles and the motion data are calculated from the position of joints frame by frame. The two sets of Kinect are placed three meters away from each other and facing to the subject. To verify the results of our system, we take the results from a motion capture system called VICON as golden standard. Our 300 test results showed that the deviation of joint moveable angles between those obtained by VICON and our system is about 4 to 8 degree in six different upper limb exercises, which are acceptable in clinical environment.