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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM68512
Volume:
10 |
10 |
Oct 2026
Pages:
1-3
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Artificial Intelligence and Machine Learning
Zeal Polytechnic , Pune
Department of Artificial Intelligence and Machine Learning
Zeal Polytechnic , Pune
Department of Artificial Intelligence and Machine Learning
Zeal Polytechnic , Pune
Department of Artificial Intelligence and Machine Learning
Zeal Polytechnic , Pune
Department of Artificial Intelligence and Machine Learning
Zeal Polytechnic , Pune
Camera-based 3D reconstruction offers a relatively low-cost way to create digital models from photographs, without requiring a dedicated industrial scanner. However, the quality of the final model depends strongly on the photographs supplied to the reconstruction software. Blurred images, inconsistent lighting, repeated views, and insufficient coverage can lead to incomplete geometry or unreliable dimensions. This paper presents a proposed AI-assisted workflow that combines image-quality assessment, capture guidance, photogrammetric reconstruction, and geometric validation for small mechanical components. The planned system will use computer-vision checks to flag unsuitable images and guide users toward additional viewpoints before reconstruction. COLMAP is proposed for Structure-from- Motion and Multi-View Stereo, while Open3D will support point-cloud inspection and measurement. The project will be evaluated by comparing a basic reconstruction workflow with the assisted workflow using the same objects and controlled capture conditions. Dimensional error, surface completeness, reconstruction success, and processing time will be recorded. At this stage, the paper describes the literature review and proposed method; experimental results have not yet been collected, and no performance improvement is claimed.
KEYWORDS
This paper proposes an affordable camera-based 3D scanning workflow for small mechanical components. Existing research and open-source tools make photogrammetric reconstruction feasible, but successful reconstruction depends on the quality and coverage of the input photographs. The proposed system adds image-quality assessment, capture guidance, and geometric validation around an established reconstruction pipeline. The key research task is to test whether these additions produce measurable benefits compared with a baseline workflow. The next stage is to build the prototype, collect repeatable experimental data, and revise this draft with actual results before journal submission.
[1] J. L. Schönberger and J.-M. Frahm, “Structure-from-Motion Revisited,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 4104–4113. doi: 10.1109/CVPR.2016.445. [2] COLMAP, “Structure-from-Motion and Multi-View Stereo: Tutorial and Documentation.” Available: https://colmap.github.io/tutorial.html. Accessed: 28-Oct-2026. [3] Y. Yao, Z. Luo, S. Li, T. Fang, and L. Quan, “MVSNet: Depth Inference for Unstructured Multi-view Stereo,” in Proceedings of the European Conference on Computer Vision (ECCV), 2018, pp. 767–783. doi: 10.1007/978-3-030-01237-3_47. [4] B. Mildenhall, P. P. Srinivasan, M. Tancik, J. T. Barron, R. Ramamoorthi, and R. Ng, “NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis,” in Proceedings of the European Conference on Computer Vision (ECCV), 2020. doi: 10.1007/978-3-030-58452-8_24. [5] Q. Bolsee, “Photogrammetry 3D Scanner Based on ESP32-CAM Module,” Fab Academy 2020 student project. Available: https://fabacademy.org/2020/labs/ulb/students/quentin-bolsee/projects/final-project/4-presentation/. Accessed: 28-Oct-2026. [6] L. Parkin, “Raspberry Pi Turntable 3D Scanner,” open-source project repository. Available: https://github.com/LouisParkin/3DScanner. Accessed: 28-Oct-2026. [7] Open3D, “Open3D: A Modern Library for 3D Data Processing.” Available: https://www.open3d.org/. Accessed: 28-Oct-2026.
Publication Date
10/30/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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