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Research Article | Open Access |

Method for Person Re-Identification with 2D-to-3D Image (Image-to-Video) Conversion

Author 1: Kohei Arai
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 16, No. 9 · Published 2025

DOI: https://doi.org/10.14569/IJACSA.2025.0160914

Abstract

A method for person re-identification using image-to-video conversion tools is proposed. The proposed method involves matching two images taken from different viewpoints: a reference image captured in advance and a current image captured in real-time to identify the person in concern in the current image, whose image is matched to the reference image. The 2D current image is converted into a 3D representation, from which synthetic images are generated at multiple viewpoints. By comparing the generated images and the reference image, person re-identification can be done. Experiments have demonstrated that the proposed method significantly improves identification accuracy. By accounting for changes in appearance due to different viewpoints and utilizing advanced image conversion, one of the main challenges in person re-identification is addressed. This approach offers a promising solution for applications requiring high accuracy in identifying individuals across varying perspectives.

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How to Cite this Article

Arai, K. (2025). Method for Person Re-Identification with 2D-to-3D Image (Image-to-Video) Conversion. International Journal of Advanced Computer Science and Applications, 16(9). https://doi.org/10.14569/IJACSA.2025.0160914

Arai, Kohei. "Method for Person Re-Identification with 2D-to-3D Image (Image-to-Video) Conversion." International Journal of Advanced Computer Science and Applications, vol. 16, no. 9, 2025, https://doi.org/10.14569/IJACSA.2025.0160914.

@article{Arai2025,
  title     = {Method for Person Re-Identification with 2D-to-3D Image (Image-to-Video) Conversion},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {9},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Kohei Arai},
  doi       = {10.14569/IJACSA.2025.0160914},
  url       = {https://doi.org/10.14569/IJACSA.2025.0160914}
}

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