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Enhancement of sparse 3D reconstruction using a modified match propagation based on particle swarm optimization

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Abstract

Sparse 3D reconstruction, based on interest points detection and matching, does not allow to obtain a suitable 3D surface reconstruction because of its incapacity to recover a cloud of well distributed 3D points on the surface of objects/scenes. In this work, we present a new approach to retrieve a 3D point cloud that leads to a 3D surface model of quality and in a suitable time. First of all, our method uses the structure from motion approach to retrieve a set of 3D points (which correspond to matched interest points). After that, we proposed an algorithm, based on the match propagation and the use of particle swarm optimization (PSO), which significantly increases the number of matches and to have a regular distribution of these matches. It takes as input the obtained matches, their corresponding 3D points and the camera parameters. Afterwards, at each time, a match of best ZNCC value is selected and a set of these neighboring points is defined. The point corresponding to a neighboring point and its 3D coordinates are recovered by the minimization of a nonlinear cost function by the use of PSO algorithm respecting the constraint of photo-consistency. Experimental results show the feasibility and efficiency of the proposed approach.

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Authors and Affiliations

  1. LIIAN, Department Of Mathematics and informatics, Faculty of Sciences Dhar-Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Soulaiman El Hazzat, Mostafa Merras, Nabil El Akkad, Abderrahim Saaidi & Khalid Satori

  2. Department of Mathematics and Computer Science, National School of Applied Sciences (ENSA) of Al-Hoceima, Mohamed First University, Oujda, Morocco

    Nabil El Akkad

  3. LSI, Department of Mathematics, Physics and Informatics, Polydisciplinary Faculty of Taza, Sidi Mohamed Ben Abdellah University, Taza, Morocco

    Abderrahim Saaidi

Authors
  1. Soulaiman El Hazzat
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  2. Mostafa Merras
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  3. Nabil El Akkad
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  4. Abderrahim Saaidi
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  5. Khalid Satori
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Correspondence to Soulaiman El Hazzat.

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El Hazzat, S., Merras, M., El Akkad, N. et al. Enhancement of sparse 3D reconstruction using a modified match propagation based on particle swarm optimization. Multimed Tools Appl 78, 14251–14276 (2019). https://doi.org/10.1007/s11042-018-6828-1

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  • DOI: https://doi.org/10.1007/s11042-018-6828-1

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