Estimating Human Skeleton Parameters and Configuration in Real-Time from Markered Optical Motion Capture

Abstract

This paper is concerned with real-time approaches to using marker-based optical motion capture to identify, parametrize, and estimate the frame by frame configuration of the human skeleton. An overview of the stages of a system is provided with the main emphasis devoted to two new methods for refining the rotation estimates used within the transformational algorithm class of joint parameter estimation methods. Virtual Marker Insertion uses additional markers inserted at the current estimates of joint location to partially enforce the concurrency of available joint location estimates. This simple algorithm is shown to outperform the methods presented in the literature. A conjugate gradient optimization on a minimal parameterization of the standard transformational algorithm cost function gives superior results, but at considerable computational cost, limiting its probable application to those frames which are actually rendered in a feedback system.