Singularity Analysis for the Perspective-Four and Five-Line Problems - Archive ouverte HAL
Article Dans Une Revue International Journal of Computer Vision Année : 2022

Singularity Analysis for the Perspective-Four and Five-Line Problems

Résumé

This paper deals with image-based visual servoing and pose estimation by observing four and five lines. Our main interest is to determine the relative configurations of the camera and the observed lines that lead to problems in control and stability. Since it is equivalent to finding the singularities of the corresponding Jacobian matrix, we use tools from computational algebraic geometry to seek configurations such that all of its minors vanish simultaneously. By choosing a suitable basis for this matrix, we revisit the problem in the case of three lines to show that one type of the singularities is when the camera lies on the hyperboloid of one sheet uniquely defined by the lines. This result is further exploited to prove that the one-dimensional singularities, if any, in the case of n lines appear when the camera lies on the transversals to the observed lines. Thus, by forcing the transversals to be complex, we can avoid the aforementioned type of singularities in the case of four lines although the algebra shows that there can always be up to 10 inevitable singular locations of the camera for the other type of singularity. For five lines, we find out that there are no singularities in the generic case. The singularities are also characterized for four and five lines with orthogonality and parallelism constraints. Furthermore, a visual servoing library is used to conduct some simulated experiments to substantiate the theoretical results. As expected, we observe problems in control in thevicinity of a singularity as well as increased errors in pose estimation.
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Dates et versions

hal-03499974 , version 1 (21-12-2021)

Identifiants

Citer

Jorge García Fontán, Abhilash Nayak, Sébastien Briot, Mohab Safey El Din. Singularity Analysis for the Perspective-Four and Five-Line Problems. International Journal of Computer Vision, 2022, 130, pp.909-932. ⟨10.1007/s11263-021-01567-4⟩. ⟨hal-03499974⟩
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