Persönlicher Status und Werkzeuge

Home People
Automatically Learning the Objective Function for Model Fitting (bibtex) [pdf]
@inproceedings{ wimmer07automatically,
  author    		= {Matthias Wimmer and Bernd Radig},
  title     		= {Automatically Learning the Objective Function for Model Fitting},
  booktitle 		= {Proceedings of the Meeting in Image Recognition and Understanding~(MIRU)},
  year      		= {2007},
  month				= {July},
  address   		= {Hiroshima, Japan},
  bib2html_pubtype	= {Refereed Conference Paper},
  bib2html_rescat   = {Image Understanding},
  bib2html_groups   = {IU},
  abstract          =
                        {Model-based image interpretation has proven to appropriately extract
                        high-level information from images. A priori knowledge about the
                        object of interest represents the basis of this task. Model fitting
                        determines the model that best matches a given image by searching for the global optimum of an objective function. Unfortunately, the objective function is usually designed manually, based on implicit and domain-dependent knowledge.
                        In contrast, this paper describes how to obtain highly accurate objective functions by learning them from annotated training images. It automates many critical decisions and the remaining manual steps hardly require domain-dependent knowledge at all. This approach yields highly accurate objective functions. Our evaluation fits a face model to a publicly available image database and compares the obtained results to a recent state-of-the-art approach.},
Powered by bibtexbrowser
Export as PDF or BIB
Back to People
Last edited 09.03.2013 19:45 by goron