The field of Human Pose Estimation is developing fast and lately leaped forward
with the release of the Kinect system. That system reaches a very good perfor-
mance for pose estimation using 3D scene information, however pose estimation
from 2D color images is not solved reliably yet. There is a vast amount of pub-
lications trying to reach this aim, but no compilation of important methods and
solution strategies. The aim of this thesis is to fill this gap: it gives an introductory
overview over important techniques by analyzing four current (2012) publications
in detail. They are chosen such, that during their analysis many frequently used
techniques for Human Pose Estimation can be explained. The thesis includes two
introductory chapters with a definition of Human Pose Estimation and exploration
of the main difficulties, as well as a detailed explanation of frequently used methods.
A final chapter presents some ideas on how parts of the analyzed approaches can
be recombined and shows some open questions that can be tackled in future work.
The thesis is therefore a good entry point to the field of Human Pose Estimation
and enables the reader to get an impression of the current state-of-the-art.