Reconstructing 3D Human Poses from Keyword Based Image Database Query

The focus of this paper lies on the creation of 3D hu- man skeleton from a set of 2D images. Unlike available approaches, which utilize a single 2D image for 3D recon- struction, the prosecuted approach utilities a set of multi- ple images, which are obtained from a simple query to the google image database. We only assume, that a query key- word can be linked to a set of images, which contain a rep- resentative subset related to the query. We expect the data to also contain false (i.e. non human-pose related) images. Our approach uses a human-pose based 3D shape context model for matching human-poses in 3D space, and filter them using a hierarchical binary clustering approach. The performance of this approach is evaluated using different query keywords.