Algorithm Performance Contest

S. Aksoy, M. Ye, M. L. Schauf, M. Song, Y. Wang, R. M. Haralick, J. R. Parker, J. Pivovarov, D. Royko, C. Sun, G. Farnebäck
Proceedings of 15th International Conference on Pattern Recognition
Volume 4, Pages 870-875
September, 2000

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Abstract

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.

Reference

Aksoy S, Ye M, Schauf ML, Song M, Wang Y, Haralick RM, Parker JR, Pivovarov J, Royko D, Sun C, Farnebäck G. Algorithm performance contest. In Proceedings of 15th International Conference on Pattern Recognition, volume 4. Barcelona, Spain: IAPR, 2000;870-875.

Bibtex entry

@InProceedings{aksoyICPR00,
  author         = {S. Aksoy and M. Ye and M. L. Schauf and M. Song and Y. Wang
                   and R. M. Haralick and J. R. Parker and J. Pivovarov and D. 
                   Royko and C. Sun and G. Farneb{\"a}ck},                     
  title          = {Algorithm Performance Contest},                            
  booktitle      = {Proceedings of 15th International Conference on Pattern    
                   Recognition},                                               
  volume         = 4,                                                          
  year           = 2000,                                                       
  organization   = {IAPR},                                                     
  address        = {Barcelona, Spain},                                         
  month          = {September},                                                
  pages          = {870--875}
}