@inproceedings{d0ebbaf1206e4ab3ba0110e39cb2bccc,
title = "Multi-resolution template kernels",
abstract = "Domains in which shapes of objects change rapidly and significantly are a challenge for existing representation techniques: sport is a good example of this. We present a texture-based approach that copes with these problems in addition to resolution variation. A set of exemplar poses are learned from subsampled example images of the target object, creating a set of multi-resolution template kernels which when convolved with the image respond suitably. This technique may then be used in established tracking algorithms (e.g. CONDENSATION). We demonstrate the technique in two domains, and suggest a Markov approach using it to model behaviour.",
author = "Needham, {C. J.} and Boyle, {R. D.}",
year = "2004",
doi = "10.1109/ICPR.2004.1334138",
language = "English",
isbn = "0769521282",
series = "Proceedings - International Conference on Pattern Recognition",
pages = "233--236",
editor = "J. Kittler and M. Petrou and M. Nixon",
booktitle = "Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004",
note = "Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 ; Conference date: 23-08-2004 Through 26-08-2004",
}