TY - JOUR
T1 - A convolutional approach to reflection symmetry
AU - Cicconet, Marcelo
AU - Birodkar, Vighnesh
AU - Lund, Mads
AU - Werman, Michael
AU - Geiger, Davi
N1 - Publisher Copyright:
© 2017
PY - 2017/8/1
Y1 - 2017/8/1
N2 - We present a convolutional approach to reflection symmetry detection in 2D. Our model, built on the products of complex-valued wavelet convolutions, simplifies previous edge-based pairwise methods. Being parameter-centered, as opposed to feature-centered, it has certain computational advantages when the object sizes are known a priori, as demonstrated in an ellipse detection application. The method outperforms the best-performing algorithm on the CVPR 2013 Symmetry Detection Competition Database in the single-symmetry case. We release code and a new, larger image database.
AB - We present a convolutional approach to reflection symmetry detection in 2D. Our model, built on the products of complex-valued wavelet convolutions, simplifies previous edge-based pairwise methods. Being parameter-centered, as opposed to feature-centered, it has certain computational advantages when the object sizes are known a priori, as demonstrated in an ellipse detection application. The method outperforms the best-performing algorithm on the CVPR 2013 Symmetry Detection Competition Database in the single-symmetry case. We release code and a new, larger image database.
KW - Mirror symmetry
KW - Reflection symmetry
UR - https://www.scopus.com/pages/publications/85020286133
U2 - 10.1016/j.patrec.2017.03.022
DO - 10.1016/j.patrec.2017.03.022
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AN - SCOPUS:85020286133
SN - 0167-8655
VL - 95
SP - 44
EP - 50
JO - Pattern Recognition Letters
JF - Pattern Recognition Letters
ER -