@INPROCEEDINGS{Stommel2008b,
  author = {Stommel, Martin and Kuhnert, Klaus-Dieter},
  title = {Part aggregation in a compositional model based on the evaluation
	of feature cooccurrence statistics},
  booktitle = {Int?l Conf. on Image and Vision Computing New Zealand},
  year = {2008},
  editor = {Irie, Kenji and Pairman, David},
  address = {Christchurch, New Zealand},
  month = {November26--28},
  publisher = {IEEE},
  abstract = {In this paper an appearance based, compositional approach to the recognition
	of deformable objects is presented. First, a hierarchical object
	model is proposed. On dierent levels of abstraction the model represents
	object categories, dierent views of an object, the parts of an object
	and basic feature vectors. Then, a training method based on multiple
	clustering steps is described. This paper addresses in particular
	the aggregation of features to parts and provides a statistical justication
	for feature clustering on the lowest level of the hierarchy. The
	performance of the proposed methods is demonstrated on a cartoon
	data base, where a high accuracy of 80{\%} is achieved.},
  doi = {10.1109/IVCNZ.2008.4762081},
  isbn = {978-1-4244-2582-2},
  owner = {pmania},
  timestamp = {2012.11.06},
  url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp={\&}arnumber=4762081}
}