Simulation of Camera Visual Range Based on Three-dimensional Model
This study proposes a camera visibility range simulation method based on 3D models, aimed at improving the accuracy of traditional 2D plane estimation methods to more realistically reflect the camera’s visibility range in three-dimensional space. The study employs various technical means to acquire 3D data and construct high-quality 3D models, including the use of professional 3D modeling software and laser scanning technology. At the same time, by setting and adjusting key parameters such as the camera’s focal length (FL), field of view (FOV), and installation position, the accuracy and authenticity of the simulation results are ensured. In the simulation calculation of visual range, an innovative method combining ray tracing and visual field analysis is adopted in this study, which realizes the accurate simulation and optimization of camera visual range. The ray tracing technology is used to simulate the propagation path of light in 3D model, and the dynamic visual field adjustment algorithm is introduced, which can automatically adjust the visual field of the camera according to the monitoring requirements, and improve the flexibility and efficiency of the monitoring system. In order to verify the effectiveness of this research method, 3D models of different scenes such as shopping malls, parks, office buildings and residential areas are selected for experiments. The experimental results show that this research method can achieve high accuracy and adaptability in different scenarios, and can achieve the best coverage of monitoring targets. Compared with the traditional manual calculation or simple software simulation, this research method has higher accuracy and stronger adaptability, which significantly improves the performance of the monitoring system. This research not only brings new breakthroughs and progress in the field of camera visual range simulation, but also provides support for the technical development in the fields of virtual reality and augmented reality.
Authors
- Min Sheng (ORCID: https://orcid.org/0000-0002-7762-5063)
- Hao Chen (ORCID: https://orcid.org/0009-0008-0473-5625)
- Yating Wang (ORCID: https://orcid.org/0000-0001-7549-2415)
Publication Details
- Published
- 2024-08-14
- DOI
- https://doi.org/10.1109/peeec63877.2024.00160
- Primary Topic
- Satellite Image Processing and Photogrammetry
- Type
- article
- Field-Weighted Citation Impact
- 0.00