Posture recognition and segmentation from 3D human body scans

Abstract

This paper addresses the problem of segmenting 3D scan data of human body (HB) into sets corresponding to the HB parts, where the posture of the body is unknown. The approach consists of recognizing first the posture, then exploiting the information retrieved from the posture recognition into the segmentation process. For the recognition, the wavelet transform coefficients are suggested as new 3D shape descriptors. Then segmentation technique integrating the model posture information is presented. The segmentation results are illustrated on human body scans of different postures.