Motion capture in uncontrolled environments
Olga Diamanti · Repository for Publications and Research Data (ETH Zurich) · 2010
The goal of a markerless motion algorithm is to recover the pose of a person from a set of images or videos.This is typically addressed in two ways: global optimization, used primarily when pose detection is the main interest, and/or local optimization, when the focus is on pose tracking.While the latter can provide very accurate results in relatively little time, it suers from sensitivity to local minima.On the contrary, the former approach ensures a correct estimation of the pose, even without any prior pose information, at the cost of much higher computational complexity.This thesis will address the pose detection problem in both these ways by enhancing an already existing tracking approach so as to obtain a robust motion capture algorithm.This will allow us to track people also in not controlled environments, such as in the case of outdoor scenarios.Additionally, we incorporated appearance modeling (by means of a texture map) with the aim to improve the tracking results.i Last but not least I would like to thank my supervisor Prof.Dr.Marc Pollefeys for giving me the opportunity to work as part of his group and get acquainted