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 threedimensional
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.