Branching Path Following for Graph Matching

Abstract

Recently, graph matching algorithms utilizing the path following strategy have exhibited state-of-the-art performances. However, the paths computed in these algorithms often contain singular points, which usually hurt the matching performance. To deal with this issue, in this paper we propose a novel path following strategy, named branching path following (BPF), which consequently improves graph matching performance. In particular, we first propose a singular point detector by solving an KKT system, and then design a branch switching method to seek for better paths at singular points. Using BPF, a new graph matching algorithm named BPF-G is developed by applying BPF to a recently proposed path following algorithm named GNCCP (Liu&Qiao 2014). For evaluation, we compare BPF-G with several recently proposed graph matching algorithms on a synthetic dataset and four public benchmark datasets. Experimental results show that our approach achieves remarkable improvement in matching accuracy and outperforms other algorithms.

Cite

Text

Wang et al. "Branching Path Following for Graph Matching." European Conference on Computer Vision, 2016. doi:10.1007/978-3-319-46475-6_32

Markdown

[Wang et al. "Branching Path Following for Graph Matching." European Conference on Computer Vision, 2016.](https://mlanthology.org/eccv/2016/wang2016eccv-branching/) doi:10.1007/978-3-319-46475-6_32

BibTeX

@inproceedings{wang2016eccv-branching,
  title     = {{Branching Path Following for Graph Matching}},
  author    = {Wang, Tao and Ling, Haibin and Lang, Congyan and Wu, Jun},
  booktitle = {European Conference on Computer Vision},
  year      = {2016},
  pages     = {508-523},
  doi       = {10.1007/978-3-319-46475-6_32},
  url       = {https://mlanthology.org/eccv/2016/wang2016eccv-branching/}
}