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Point Cloud Data Reduction Algorithm Based on SIFT3D Features

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Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021) (AICV 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1377))

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Abstract

As the original point cloud data reflecting the shape information of three-dimensional objects is often data too large which will adversely affect the point cloud registration, three-dimensional reconstruction, and other follow-up operations. Uniform grid method, curvature sampling method, and other methods are classical point cloud data reduction algorithms. This paper presents a new point cloud reduction algorithm based on SIFT3D feature points. Compared with the traditional uniform mesh method and curvature sampling method, it can be found that, on the premise of retaining the feature points, the 3D solid simplified by this method still obtains better results in the standard deviation and surface area.

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Author information

Authors and Affiliations

  1. School of Electronic, Electrical Engineering and Physics, Fujian University of Technology, Fuzhou, 350118, China

    Haiyun Zhang, Jian Dong, Jian Lu, Yufeng Ling & Yiwen Ou

  2. National Demonstration Center for Experimental Electronic Information and Electrical Technology Education, Fujian University of Technology, Fuzhou, 350118, China

    Zhiming Cai

Authors
  1. Haiyun Zhang
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  2. Jian Dong
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  3. Jian Lu
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  4. Yufeng Ling
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  5. Yiwen Ou
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  6. Zhiming Cai
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Editor information

Editors and Affiliations

  1. Information Technology Department, Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Sciences and Techniques, Hassan 1st University, Settat, Morocco

    Abdelkrim Haqiq

  3. School of Medicine, University of Missouri, Columbia, MO, USA

    Peter J. Tonellato

  4. ISAE-ENSMA, Futuroscope Chasseneuil Cedex, France

    Ladjel Bellatreche

  5. British University Vietnam, Hung Yen, Vietnam

    Sam Goundar

  6. Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt

    Ahmad Taher Azar

  7. NEST Research Group, ENSEM, Hassan II University of Casablanca, Casablanca, Morocco

    Essaid Sabir

  8. High National School for Computer Science and Systems Analysis (ENSIAS), Mohammed V University, Rabat, Morocco

    Driss Bouzidi

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Zhang, H., Dong, J., Lu, J., Ling, Y., Ou, Y., Cai, Z. (2021). Point Cloud Data Reduction Algorithm Based on SIFT3D Features. In: Hassanien, A.E., et al. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). AICV 2021. Advances in Intelligent Systems and Computing, vol 1377. Springer, Cham. https://doi.org/10.1007/978-3-030-76346-6_33

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