ABSTRACT
This paper describes the design and implementation of a multiple view stereoscopic 3D vision system and a supporting infant tracker pipeline to track limb movement in natural play environments and identify potential metrics to quantify movement behavior. So far, human pose estimation and tracking with 3D cameras has been focused primarily on adults and cannot be directly extended to infants because of differences in visual features such as shapes, sizes and appearance. With rehabilitation in mind, we propose a portable, compact, markerless, low cost and high resolution 3D vision system and a tracking algorithm that exploits infant appearance attributes and depth information. This approach achieved a mean 3D tracking error of 8.21cm and a standard deviation of 8.75cm. We also identify two potential metrics for movement behavior analysis - approximate entropy and interaction events.
