Abstract
Due to the important role that accurate pose estimation plays in the field of vision measurement, a careful tracing and analysis of errors introduced in all aspects is necessary. In this paper, we launch an in-depth and meticulous research to seek for and analyze factors causing pose errors. These factors contain camera intrinsic parameters, 3D world coordinates of feature points, corresponding 2D image coordinates and different pose estimation algorithms. They are usually ignored in practical applications, leading to inaccurate pose. We develop mathematical tools to construct error models to estimate the actual error occurring in the implementation of a pose estimation algorithm. Our central idea is to make only one variable different at a time by controlling various variables. Then the effect of that single factor can be determined. Afterwards our approach is applied to ample synthetic experiments. The relationship between the influencing factors and pose estimation error is established and provides reference and basis to control errors and achieve more accurate pose.
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© 2014 Springer International Publishing Switzerland
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Song, Y., Wang, F., Gao, S., Yang, H., He, Y. (2014). Error Tracing and Analysis of Vision Measurement System. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_80
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DOI: https://doi.org/10.1007/978-3-319-09333-8_80
Publisher Name: Springer, Cham
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