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Robust and Efficient Ellipse Fitting Using Tangent Chord Distance

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Computer Vision – ACCV 2018 (ACCV 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11363))

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Abstract

Ellipse fitting is a fundamental problem in computer vision which has been extensively studied during the past decades. However, this problem still remains unresolved due to many practical challenges such as occlusion, background clutter, noise and outlier, and so forth. In this paper, we introduce a novel geometric distance, called Tangent Chord Distance (TCD), to formulate the ellipse fitting problem. Under the least squares framework, TCD is used as the measure to quantify the fitting error, based on which a nonlinear objective function is established and minimized via the Gauss-Newton method. Compared to existing geometric distance based methods, a key merit of our approach is that, the very time-consuming iterative procedure of finding the counterparts of the given points has a simple closed-form solution in our TCD-based formulation, which can thereby significantly reduce the computational load without sacrificing the performance. Experimental results on both synthetic data and public image datasets have demonstrated the superiority of our method over other compared methods in terms of robustness and efficiency.

Fundamental Research Funds for the Central Universities, SCUT under Grant 2018MS72.

Guangzhou Science and Technology Program under the Grant 201904010299.

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Notes

  1. 1.

    http://imagelab.ing.unimore.it/imagelab/ellipse/ellipse_dataset.zip.

  2. 2.

    http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/PILU1/demo.html.

  3. 3.

    https://sites.google.com/site/dilipprasad/Source-codes.

  4. 4.

    http://www.users.on.net/~zygmunt.szpak/.

  5. 5.

    https://github.com/sebdi/ellipse-fitting.

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Acknowledgment

This work is supported by National Natural Science Foundation of China under the Grant 61703166.

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Authors and Affiliations

  1. South China University of Technology, Guangzhou, China

    Jiarong Ou, Jin-Gang Yu, Lichao Xiao & Zhifeng Liu

  2. Huazhong University of Science and Technology, Wuhan, China

    Changxin Gao

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  1. Jiarong Ou
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  2. Jin-Gang Yu
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  3. Changxin Gao
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  4. Lichao Xiao
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  5. Zhifeng Liu
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Corresponding author

Correspondence to Jin-Gang Yu .

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Editors and Affiliations

  1. IIIT Hyderabad, Hyderabad, India

    C. V. Jawahar

  2. ANU, Canberra, ACT, Australia

    Hongdong Li

  3. Simon Fraser University, Burnaby, BC, Canada

    Greg Mori

  4. ETH Zurich, Zurich, Zürich, Switzerland

    Konrad Schindler

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Ou, J., Yu, JG., Gao, C., Xiao, L., Liu, Z. (2019). Robust and Efficient Ellipse Fitting Using Tangent Chord Distance. In: Jawahar, C., Li, H., Mori, G., Schindler, K. (eds) Computer Vision – ACCV 2018. ACCV 2018. Lecture Notes in Computer Science(), vol 11363. Springer, Cham. https://doi.org/10.1007/978-3-030-20893-6_12

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  • DOI: https://doi.org/10.1007/978-3-030-20893-6_12

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