Manufacturing Technology 2023, 23(4):532-537 | DOI: 10.21062/mft.2023.060

Research on Viewpoint Planning Method for Multi-view Image 3D Reconstruction

Yun Shi ORCID..., Yanyan Zhu ORCID...
West Anhui University, Luan, China

A model-based viewpoint planning and filtering method is proposed to determine the position and pose of viewpoints in 3D reconstruction of multi-view images. The method first determines the necessary parameters to control the camera position and attitude. Second, the mathematical error model is developed and combined with stereo overlap to guide viewpoint selection. According to the shooting distance, a dense candidate view area is then established, the subview collection is screened, & a view supplement scheme is proposed for the area where the candidate view cannot be shot, improving the integrity of the resulting data. Experimental results demonstrate that our viewpoint planning method has high shooting coverage & highly accurate 3D reconstruction.

Keywords: Multi-view, 3D reconstruction, Aerial-photography, View Planning
Grants and funding:

This research was supported by the School-level Research Projects of West Anhui University (WXZR202211), West Anhui University high-level Personnel Research Funding Project (WGKQ2022015),Anhui Provincial Quality Engineering Project (2021sysxzx031, 2022sx171), School level Quality Engineering Project of West Anhui University (wxxy2022085),the Open Fund of Anhui Undergrowth Crop Intelligent Equipment Engineering Research Center (AUCIEERC-2022-05)

Received: May 23, 2023; Revised: July 20, 2023; Accepted: August 9, 2023; Prepublished online: August 9, 2023; Published: September 5, 2023  Show citation

ACS AIP APA ASA Harvard Chicago IEEE ISO690 MLA NLM Turabian Vancouver
Shi Y, Zhu Y. Research on Viewpoint Planning Method for Multi-view Image 3D Reconstruction. Manufacturing Technology. 2023;23(4):532-537. doi: 10.21062/mft.2023.060.
Download citation

References

  1. LI, A.Y., YUAN, J.Y., PUN, C., BARENSE, M.D. (2023). The effect of memory load on object reconstruction: Insights from an online mouse-tracking task, Attention, Perception, & Psychophysics, Vol. 163, No.1, pp. 1-19. Go to original source...
  2. MA, K., WANG, X., HE, S., ZHANG, X., ZHANG, Y.X. (2023). Learning to image and track moving objects through scattering media via speckle difference, Optics and Laser Technology, Vol.159, pp. 108925. Go to original source...
  3. MATUŠ, M., BECHNÝ, V., JOCH, R., DRBÚL, M., HOLUBJÁK, J., CZÁN, A., NOVÁK, M. & ŠAJGALÍK, M. 2023. Geometric Accuracy of Components Manufactured by SLS Technology Regarding the Orientation of the Model during 3D Printing. Manufacturing Technology, 23, 233-40. Go to original source...
  4. ZHANG, Y., SHAO, H.C., PAN, T., MENGKE, T. (2023). Dynamic cone-beam CT reconstruction using spatial and temporal implicit neural representation learning (STINR), Physics in Medicine & Biology, Vol. 68, No. 4, pp. 045005. Go to original source...
  5. MAST, T.D., JOHNSTONE, D.A., DUMOULIN, C.L., LAMBA, M.A., PATCH, S.K. (2023). Reconstruction of thermoacoustic emission sources induced by proton irradiation using numerical time reversal, Physics in Medicine & Biology, Vol. 68, No. 2, pp. 025003. Go to original source...
  6. SEDLAK, J., JOSKA, Z., HRBACKOVA, L., JURICKOVA, E., HRUSECKA, D. & HORAK, O. 2022. Determination of Mechanical Properties of Plastic Components Made by 3D Printing. Manufacturing Technology, 22, 733-46. Go to original source...
  7. THIRUMALAI, A., RAMAN, P.G., JAYAVELU, T. (2023). Bridging the gap between maleate hydratase, citraconase and isopropylmalate isomerase: Insights into the single broad-specific enzyme, Enzyme and Microbial Technology, Vol. 162, pp. 110140. Go to original source...
  8. BAUER, D., WU, Q., MA, K.L. (2023). FoVolNet: Fast Volume Rendering using Foveated Deep Neural Networks, IEEE Transactions on Visualization and Computer Graphics, Vol. 29, No. 1, pp. 515-525. Go to original source...
  9. TONG, Y.D., CAI, Y.Z., NEVIN, A., MA, Q.L. (2023). Digital technology virtual restoration of the colours and textures of polychrome Bodhidharma statue from the Lingyan Temple, Shandong, China, Heritage Science, Vol. 11, No. 1, pp. 1-17. Go to original source...
  10. PERNICA, J., VODÁK, M., ŠAROCKÝ, R., ŠUSTR, M., DOSTÁL, P., ČERNÝ, M. & DOBROCKÝ, D. 2022. Mechanical Properties of Recycled Polymer Materials in Additive Manufacturing. Manufacturing Technology, 22, 200-3. Go to original source...
  11. MARTEL, C., ARNALSTEEN, C., LECOINTRE, L., LAPOINTE, M., ROY, C., FALLER, E., BOISRAMÉ, T., SOLER, L., AKLADIOS, C. (2023). Feasibility and clinical value of virtual reality for deep infiltrating pelvic endometriosis: A case report, Journal of Gynecology Obstetrics and Human Reproduction, Vol. 52, No. 1, 102500. Go to original source...
  12. LICHOVNÍK, J., MIZERA, O., SADÍLEK, M., ČEPOVÁ, L., ZELINKA, J. & ČEP, R. 2020. Influence of Tumbling Bodies on Surface Roughness and Geometric Deviations by Additive SLS Technology. Manufacturing Technology, 20, 342-6. Go to original source...
  13. DIEZINGER, M.A., TAMADAZTE, B., LAURENT, G.J. (2022). 3d curvature-based tip load estimation for continuum robots, IEEE Robotics and Automation Letters, Vol. 7, No. 4, pp. 10526-10533. Go to original source...
  14. DU, G., DENG, Y., NG, W.W., LI, D. (2022). An Intelligent Interaction Framework for Teleoperation Based on Human-Machine Cooperation, IEEE Transactions on Human-Machine Systems, Vol. 52, No. 5, pp.963-972. Go to original source...
  15. JEON, M.H., KIM, J., RYU, J.H., KIM, A. (2022). Ambiguity-Aware Multi-Object Pose Optimization for Visually-Assisted Robot Manipulation, IEEE Robotics and Automation Letters, Vol. 8, No. 1, pp.137-144. Go to original source...
  16. SCOTT, W.R., ROTH, G. (2023). View Planning for Automated Three-Dimensional Object Reconstruction and Inspection, ACM Computing Surveys, Vol. 35, No. 1, pp.61-96. Go to original source...
  17. FABIAN, M., HUŇADY, R. & KUPEC, F. 2022. Reverse Engineering and Rapid Prototyping in the Process of Developing Prototypes of Automotive Parts. Manufacturing Technology, 22, 669-78. Go to original source...
  18. PONIKELSKY, J., ZURAVSKY, I., CERNOHLAVEK, V., CAIS, J. & STERBA, J. 2021. Influence of Production Technology on Selected Polymer Properties. Manufacturing Technology, 21, 520-30. Go to original source...
  19. QIAN, R., LAI, X., LI, X.R. (2022). 3D Object Detection for Autonomous Driving: A Survey, Pattern Recognition, Vol. 130, pp. 108796. Go to original source...
  20. ZACCHINI, L., FRANCHI, M., RIDOLFI, A. (2022). Sensor-driven autonomous underwater inspections: A receding-horizon RRT-based view planning solution for AUVs, Journal of Field Robotics, Vol. 39, No. 5, pp.499-527. Go to original source...
  21. OLAGUE, G. (2007). Design and Simulation of Photogrammetric networks using Genetic algorithms, ASPRS 2000 Annual Conference Proceeding.
  22. MENDRICKY, R. & SOBOTKA, J. 2020. Accuracy Comparison of the Optical 3D Scanner and CT Scanner. Manufacturing Technology, 20, 791-801. Go to original source...
  23. DUNN, E., OLAGUE, G. (2004). Milti-objective Sensor Planning for Efficient and Accurate Object Reconstruction, EvoWorkshops, pp. 312-321. Go to original source...
  24. SCHMID, K., HIRSCHMULLER, H. (2012). View Planning for Multi-View Stereo 3D Reconstruction Us-ing an Autonomous Multicopter, Intel Robot Syst, Vol. 65, pp.309-323. Go to original source...
  25. ZHEN, X. (2014). UAV aerial image-based three-dimensional reconstruction of outdoor scenes, Zhejiang University of Technology.
  26. GOSPODNETIĆ, P., MOSBACH, D., RAUHUT, M., HAGEN, H. (2022). Viewpoint placement for inspection planning, Machine Vision and Applications, Vol. 33, No. 2, pp. 1-21. Go to original source...

This is an open access article distributed under the terms of the Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.