Perceptual Organization Module Comparison

Sudhir Borra and Sudeep Sarkar


We have developed five performance measures to evaluate grouping modules in the context of constrained search and indexing based object recognition. Using these measures, we demonstrated a sound experimental framework based on statistical ANOVA tests to compare and contrast three edge based organization modules, namely those of Etemadi et al., Jacobs, and Sarkar-Boyer in the domain of aerial objects using 50 images. With adapted parameters, the Jacobs module performs overall the best for constraint based recognition. For fixed parameters, the Sarkar-Boyer module is the best in terms of recognition accuracy and indexing speedup. Etemadi et al.'s module performs equally well with fixed and adapted parameters while the Jacobs module is most sensitive to fixed and adapted parameter choices. The overall performance ranking of the modules is Jacobs, Sarkar-Boyer, and Etemadi et al.

Detailed description of this work can be found in

  • S. Borra and S. Sarkar, ``A Framework for Performance Characterization of Intermediate Level Grouping Modules,'' IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 11, pp. 1306--1312, Nov. 1997.
  • S. Borra and S. Sarkar, `` Experimental Performance Evaluation of Feature Grouping Modules,'' IEEE Conference on Computer Vision and Pattern Recognition, (San Juan), pp. 891--896, June 1997.

    We would be glad to include your grouping code in future studies (free of charge!!) if you would just drop us a line with your source code and a detailed description of your algorithm.

    This work was supported by the National Science Foundation CAREER grant No. IRI-9501932.