An Analysis of Successful Approaches to Human Pose Estimation


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.