Symmetry Detection from RealWorld Images Competition 2013: Summary and Results

Jingchen Liu, George Slota, Gang Zheng, Zhaohui Wu, Minwoo Park, Seungkyu Lee, Ingmar Rauschert, Yanxi Liu; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2013, pp. 200-205

Abstract

Symmetry is a pervasive phenomenon presenting itself in all forms and scales in natural and manmade environments. Its detection plays an essential role at all levels of human as well as machine perception. The recent resurging interest in computational symmetry for computer vision and computer graphics applications has motivated us to conduct a US NSF funded symmetry detection algorithm competition as a workshop affiliated with the Computer Vision and Pattern Recognition (CVPR) Conference, 2013. This competition sets a more complete benchmark for computer vision symmetry detection algorithms. In this report we explain the evaluation metric and the automatic execution of the evaluation workflow. We also present and analyze the algorithms submitted, and show their results on three test sets of real world images depicting reflection, rotation and translation symmetries respectively. This competition establishes a performance baseline for future work on symmetry detection.

Related Material

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[bibtex]
@InProceedings{Liu_2013_CVPR_Workshops,
author = {Liu, Jingchen and Slota, George and Zheng, Gang and Wu, Zhaohui and Park, Minwoo and Lee, Seungkyu and Rauschert, Ingmar and Liu, Yanxi},
title = {Symmetry Detection from RealWorld Images Competition 2013: Summary and Results},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2013}
}