Abstract
The performance of vision-based simultaneous localization and mapping (VSLAM) algorithms is affected by physical space, environment variables, and other factors, which require massive verifications in diverse scenarios in the real world. However, collecting visual data for VSLAM algorithms in the real world is an expensive and time-consuming process. With the development of rendering technology, it is possible to directly generate data sets using synthetic images with a virtual camera using computer simulation. In order to simulate realistic images with a virtual camera, precise modeling of the geometric characteristics of the vision sensor must be addressed. In this paper, we propose a geometric consistency model considering both the projection characteristics and the lens distortion of a camera. We also provide an efficient implement of the proposed geometric consistency model, which can be used to generate data sets or evaluate algorithms.
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Acknowledgment
This work was supported by the National Nature Science Foundation of China (NSFC) under Grant 61873163, Grant 61402283, and the Shanghai Science and Technology Committee under Grant 20511103103, and Equipment Pre-Research Field Foundation under Grant 61405180205, Grant 61405180104.
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Zhu, Y. et al. (2021). A Geometric Consistency Model of Virtual Camera for Vision-Based SLAM Simulation. In: Meng, X., Xie, X., Yue, Y., Ding, Z. (eds) Spatial Data and Intelligence. SpatialDI 2020. Lecture Notes in Computer Science(), vol 12567. Springer, Cham. https://doi.org/10.1007/978-3-030-69873-7_20
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DOI: https://doi.org/10.1007/978-3-030-69873-7_20
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