Algorithm performance contest

Selim Aksoy, Ming Ye, Michael L. Schauf, Mingzhou Song, Yalin Wang, Robert M. Haralick, Jim R. Parker, Juraj Pivovarov, Dominik Royko, Changming Sun, Gunnar Farnebäck

Research output: Chapter in Book/Report/Conference proceedingChapter

17 Scopus citations


This contest involved the running and evaluation of computer vision and pattern recognition techniques on different data sets with known groundtruth. 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. This paper summarizes the data generation for each area and experimental results for a total of six participating algorithms.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Pattern Recognition
Number of pages6
StatePublished - 2000
Externally publishedYes

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture


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