3D hand shape analysis for palm and fingers identification

This paper proposes a novel scheme for the extraction and identification of the palm and the fingers from a single depth map. The hand is firstly segmented from the rest of the scene, then it is divided into palm and fingers regions. For this task we employed a novel scheme that exploits the idea that fingers have a tubular shape while the palm is more planar. Following this rationale we applied a contraction guided by the normals in order to reduce the fingers into thinner structures that can be identified by analyzing the changes in the point density. Density-based clustering is then applied and finally a linear programming based approach is employed to identify the various fingers. Experimental results prove the effectiveness of the proposed approach even in complex situations and in presence of inter-occlusions between the various fingers.