TY - GEN
T1 - Symmetry detection from realworld images competition 2013
T2 - 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2013
AU - Liu, Jingchen
AU - Slota, George
AU - Zheng, Gang
AU - Wu, Zhaohui
AU - Park, Minwoo
AU - Lee, Seungkyu
AU - Rauschert, Ingmar
AU - Liu, Yanxi
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84884924709&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84884924709&partnerID=8YFLogxK
U2 - 10.1109/CVPRW.2013.155
DO - 10.1109/CVPRW.2013.155
M3 - Conference contribution
AN - SCOPUS:84884924709
SN - 9780769549903
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SP - 200
EP - 205
BT - Proceedings - 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2013
Y2 - 23 June 2013 through 28 June 2013
ER -