Publications Freek Stulp

@InProceedings{wimmer07estimating,
  title                    = {Estimating Natural Activity by Fitting 3D~Models via Learned Objective Functions},
  author                   = {Matthias Wimmer and Christoph Mayer and Freek Stulp and Bernd Radig},
  booktitle                = {Vision, Modeling and Visualization Workshop (VMV)},
  year                     = {2007},
  note                     = {Non-archival.},
  abstract                 = { Model-based image interpretation has proven to robustly extract high-level scene descriptors from raw image data. Furthermore, geometric texture models represent a fundamental component for visualizing real-world scenarios. However, the motion of the model and the real-world object must be similar in order to portray natural activity. Again, this information can be determined by inspecting images via model-based image interpretation. This paper sketches the challenge of fitting models to images, describes the shortcomings of current approaches and proposes a technique based on machine learning techniques. We identify the objective function as a crucial component for fitting models to images. Furthermore, we state preferable properties of these functions and we propose to learn such a function from manually annotated example images. },
  bib2html_pubtype         = {Refereed Workshop Paper},
  bib2html_rescat          = {Learning Objective Functions for Face Model Fitting}
}