Pose-Independent Joint Extraction from Scanned Human Body

With the development of 3D scanning technique, joint extraction from scanned human body model is one of the most active research areas in virtual human modeling. Many different approaches have been proposed with the aim of extracting joints from scanned human body. But most of these methods can not guarantee pose-independence, while other methods which can ensure pose-independence require manual intervention. To solve this problem, a new framework is presented for automatic pose-independent joint extraction from scanned human body. Firstly, a new Morse function is defined on the scanned human body shape as geodesic distance from points to a source point which can be extracted by a heuristic method. Secondly, the Morse function is calculated, and then feature points and topological structure of the model shape can be extracted automatically according to Morse theory. Finally, shape is divided into segments based on Morse function isolines, and joints can be extracted from the corresponding segments of the human body shape by analyzing the circularity of Morse function isolines of the model. Experiments have been done on 20 scanned human bodies with about 5000 faces and 2300 points in each body shape. The experiment results demonstrate that this method is a pose-independent and automatic method, and is more accurate than previous methods.