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Search: (WFRF:(Ye L.)) srt2:(2000-2004) srt2:(2000) > Algorithm Performan...

Algorithm Performance Contest

Aksoy, Selim (author)
Intelligent Systems Laboratory, University of Washington, Seattle, USA
Ming, Ye (author)
Intelligent Systems Laboratory, University of Washington, Seattle, USA
Schauf, Michael L. (author)
Intelligent Systems Laboratory, University of Washington, Seattle, USA
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Song, Mingzhou (author)
Intelligent Systems Laboratory, University of Washington, Seattle, USA
Wang, Yalin (author)
n/a,Intelligent Systems Laboratory, University of Washington, Seattle, USA
Haralick, Robert M. (author)
Intelligent Systems Laboratory, University of Washington, Seattle, USA
Parker, Jim R. (author)
University of Calgary, Dept. of Computer Science, Calgary, Canada
Pivovarov, Juraj (author)
University of Calgary, Dept. of Computer Science, Calgary, Canada
Royko, Dominik (author)
University of Calgary, Dept. of Computer Science, Calgary, Canada
Sun, Changming (author)
CSIRO Mathematical and Information Sciences, Australia
Farnebäck, Gunnar (author)
Linköpings universitet,Tekniska högskolan,Bildbehandling
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 (creator_code:org_t)
IEEE, 2000
2000
English.
In: Proceedings. 15th International Conference on Pattern Recognition, 2000. - : IEEE. - 0769507506 ; , s. 870-876
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • This contest involved the running and evaluation of computer vision and pattern recognition techniques on different data sets with known groundwidth. The contest included three areas; binary shape recognition, symbol recognition and image flow estimation. A package was made available for each area. Each package contained either real images with manual groundtruth or programs to generate data sets of ideal as well as noisy images with known groundtruth. They also contained programs to evaluate the results of an algorithm according to the given groundtruth. These evaluation criteria included the generation of confusion matrices, computation of the misdetection and false alarm rates and other performance measures suitable for the problems. The paper summarizes the data generation for each area and experimental results for a total of six participating algorithms

Keyword

TECHNOLOGY
TEKNIKVETENSKAP

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