Publications Freek Stulp

@InProceedings{wimmer07enabling,
  title                    = {Enabling Users to Guide the Design of Robust Model Fitting Algorithms},
  author                   = {Matthias Wimmer and Freek Stulp and Bernd Radig},
  booktitle                = {Proceedings of the Eleventh IEEE International Conference on Computer Vision (ICCV)},
  year                     = {2007},
  abstract                 = { Model-based image interpretation extracts high-level information from images using a priori knowledge about the object of interest. The computational challenge in model fitting is to determine the model parameters that best match a given image, which corresponds to finding the global optimum of the objective function. When it comes to the robustness and accuracy of fitting models to specific images, humans still outperform state-of-the-art model fitting systems. For this reason, we propose a method in which non-experts can guide the process of designing model fitting algorithms. In particular, this paper demonstrates how to obtain robust objective functions for face model fitting applications, by learning their calculation rules from example images annotated by humans. We evaluate the obtained function using a publicly available image database and compare it to a recent state-of-the-art approach in terms of accuracy. },
  bib2html_pubtype         = {Refereed Conference Paper},
  bib2html_rescat          = {Learning Objective Functions for Face Model Fitting},
  url                      = {http://www.computer.org/portal/web/csdl/doi/10.1109/ICCV.2007.4409121}
}