Relative Motion Recovery Reconstruction Algorithm for Fixed Cameras

Aiming at the problem that the structure from motion algorithm needs to change the position of the camera in the process of camera shooting, we utilize the relationship between the relative motion of the object and the camera to obtain the image sequence containing the multi-angle view of the object. A relative structure from motion is designed and realized by locating the region where the object is located in the image sequence and constraining the applicable range of feature point extraction. The experimental results show that the SFRM algorithm is applicable to the fixed position of the camera, and can increase the proportion of matched pairs located in the object region from 32% to 84% of the total number of matched pairs, and improve the time efficiency by 38.29% compared with the traditional SFM algorithm, thus successfully expanding the applicability of the SFM algorithm.

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Publication Details

Published
2024-08-04
DOI
https://doi.org/10.1109/icma61710.2024.10632905
Primary Topic
Advanced Vision and Imaging
Type
article
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article

Relative Motion Recovery Reconstruction Algorithm for Fixed Cameras

Bing Li, Yirui Wang, Yibo Zhen
Advanced Vision and Imaging
article

Relative Motion Recovery Reconstruction Algorithm for Fixed Cameras

Bing Li, Yirui Wang, Yibo Zhen
article en

Abstract

Aiming at the problem that the structure from motion algorithm needs to change the position of the camera in the process of camera shooting, we utilize the relationship between the relative motion of the object and the camera to obtain the image sequence containing the multi-angle view of the object. A relative structure from motion is designed and realized by locating the region where the object is located in the image sequence and constraining the applicable range of feature point extraction. The experimental results show that the SFRM algorithm is applicable to the fixed position of the camera, and can increase the proportion of matched pairs located in the object region from 32% to 84% of the total number of matched pairs, and improve the time efficiency by 38.29% compared with the traditional SFM algorithm, thus successfully expanding the applicability of the SFM algorithm.

Harbin Engineering University (CN)
Openalex Percentile: Top 87%
Advanced Vision and Imaging
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