A Convolutional Approach to Reflection Symmetry

Pattern Recognition Letters, 2017

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. Code and a new database for 2D symmetry detection is available.

Paper: arXiv, PRL | Code | Database


  author        = {M. Cicconet and V. Birodkar and M. Lund and M. Werman and D. Geiger},
  title         = {A convolutional approach to reflection symmetry},
  howpublished  = {https://doi.org/10.1016/j.patrec.2017.03.022},
  year          = {2017},
  note          = {Pattern Recognition Letters}