Tracking of Human Body Parts using the Multiocular Contracting Curve Density Algorithm

In this contribution we introduce the Multiocular Contracting Curve Density algorithm (MOCCD), a novel method for fitting a 3D parametric curve. The MOCCD is integrated into a tracking system and its suitability for tracking human body parts in 3D in front of cluttered background is examined. The developed system can be applied to a variety of body parts, as the object model is replaceable in a simple manner. Based on the example of tracking the human hand-forearm limb it is shown that the use of three MOCCD algorithms with three different kinematic models within the system leads to an accurate and temporally stable tracking. All necessary information is obtained from the images, only a coarse initialisation of the model parameters is required. The investigations are performed on 14 real-world test sequences. These contain movements of different hand-forearm configurations in front of a complex cluttered background. We find that the use of three cameras is essential for an accurate...

• Type: Conference
• Year: 2007
• Where: 3DIM
• Authors: Markus Hahn, Lars Krüger, Christian Wöhler, Horst-Michael Gross
• Keywords: 3DIM 2007, Body Parts, Cluttered Background, Contracting Curve Density, Image Processing