maximize


@inproceedings{StIhMa03,
  author = {Robert Strzodka and Ivo Ihrke and Marcus Magnor},
  title = {A Graphics Hardware Implementation of the Generalized Hough Transform
	for fast Object Recognition, Scale, and 3D Pose Detection},
  booktitle = {International Conference on Image Analysis and Processing (ICIAP
	2003)},
  year = {2003},
  pages = {188--193},
  abstract = {The generalized Hough transform constitutes a well-known approach
	to object recognition and pose detection. To attain reliable detection
	results, however, a very large number of candidate object poses and
	scale factors need to be considered. In this paper we employ an inexpensive,
	consumer-market graphics card as the ``poor man's'' parallel processing
	system. We describe the implementation of a fast and enhanced version
	of the generalized Hough transform on graphics hardware. Thanks to
	the high bandwidth of on-board texture memory, a single pose can
	be evaluated in less than 3~ms, independent of the number of edge
	pixels in the image. From known object geometry, our hardware-accelerated
	generalized Hough transform algorithm is capable of detecting an
	object's 3D pose, scale, and position in the image within less than
	one minute. A good pose estimation is delivered in even less than
	10 seconds.},
  html = {http://numerik.math.uni-duisburg.de/people/strzodka/projects/CV/}
}