Skeletal Detection Enhancement using Kinect

Abstract

Computer vision is applied in many software and devices. The detection and reconstruction of the human skeletal structure is one of area of interest, where the camera will identify the human parts and construct the joints of the person standing in front. Three-dimensional pose estimation is solved using various learning approaches, such as Support Vector Machines and Gaussian processes. However, difficulties in cluttered scenarios are encountered, and require additional input data, such as silhouettes, or controlled camera settings. The paper focused on estimating the three dimensional pose of a person without requiring background information, which is robust to camera variations. Each of the joint has three-dimensional space position and matrix orientation with respect to the sensor. Matlab Simulink was utilized to provide communication tools with depth camera using Kinect device for skeletal detection. Results on the skeletal detection using Kinect sensor is analysed in measuring the abilities to detect skeletal structure accurately, and it is shown that the system is able to detect human skeletal performing non-complex basic motions in daily life.