A Robust Approach for Singular Point Extraction Based on Complex Polynomial Model

Jin Qi, Suxing Liu; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2014, pp. 78-83

Abstract

This paper focuses on a general framework for singular point extraction from vector field.We design a new index of singular point based on complex polynomial model. We test our method in the publicly available benchmark dataset of the singular point detection competition (SPD2010).Our algorithm gets the best results and produces large margins compared to the top five algorithms which took part in the public competition.We also compare our algorithm with the state-of-the-art singular point detection algorithm (called "ZPM" method) with the benchmark. The performance of our method is much better than that of the state-of-the-art method.

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[bibtex]
@InProceedings{Qi_2014_CVPR_Workshops,
author = {Qi, Jin and Liu, Suxing},
title = {A Robust Approach for Singular Point Extraction Based on Complex Polynomial Model},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2014}
}