65,909 research outputs found

    Depth-Dependent High Distortion Lens Calibration

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    [EN] Accurate correction of high distorted images is a very complex problem. Several lens distortion models exist that are adjusted using different techniques. Usually, regardless of the chosen model, a unique distortion model is adjusted to undistort images and the camera-calibration template distance is not considered. Several authors have presented the depth dependency of lens distortion but none of them have treated it with highly distorted images. This paper presents an analysis of the distortion depth dependency in strongly distorted images. The division model that is able to represent high distortion with only one parameter is modified to represent a depth-dependent high distortion lens model. The proposed calibration method obtains more accurate results when compared to existing calibration methods.The Instituto de Automatica e Informatica Industrial (ai2) of the Universitat Politecnica de Valencia has financed the open access fees of this paper.Ricolfe Viala, C.; Esparza Peidro, A. (2020). Depth-Dependent High Distortion Lens Calibration. Sensors. 20(13):1-12. https://doi.org/10.3390/s20133695S1122013Ricolfe-Viala, C., & Sanchez-Salmeron, A.-J. (2010). Lens distortion models evaluation. Applied Optics, 49(30), 5914. doi:10.1364/ao.49.005914Wieneke, B. (2008). Volume self-calibration for 3D particle image velocimetry. Experiments in Fluids, 45(4), 549-556. doi:10.1007/s00348-008-0521-5Magill, A. A. (1955). Variation in Distortion with Magnification*. Journal of the Optical Society of America, 45(3), 148. doi:10.1364/josa.45.000148Fryer, J. G., & Fraser, C. S. (2006). ON THE CALIBRATION OF UNDERWATER CAMERAS. The Photogrammetric Record, 12(67), 73-85. doi:10.1111/j.1477-9730.1986.tb00539.xAlvarez, L., Gómez, L., & Sendra, J. R. (2010). Accurate Depth Dependent Lens Distortion Models: An Application to Planar View Scenarios. Journal of Mathematical Imaging and Vision, 39(1), 75-85. doi:10.1007/s10851-010-0226-2Ricolfe-Viala, C., Sanchez-Salmeron, A.-J., & Martinez-Berti, E. (2011). Accurate calibration with highly distorted images. Applied Optics, 51(1), 89. doi:10.1364/ao.51.000089Ricolfe-Viala, C., & Sánchez-Salmerón, A.-J. (2010). Robust metric calibration of non-linear camera lens distortion. Pattern Recognition, 43(4), 1688-1699. doi:10.1016/j.patcog.2009.10.003Devernay, F., & Faugeras, O. (2001). Straight lines have to be straight. Machine Vision and Applications, 13(1), 14-24. doi:10.1007/pl0001326

    A graph-based mathematical morphology reader

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    This survey paper aims at providing a "literary" anthology of mathematical morphology on graphs. It describes in the English language many ideas stemming from a large number of different papers, hence providing a unified view of an active and diverse field of research

    Disparity and Optical Flow Partitioning Using Extended Potts Priors

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    This paper addresses the problems of disparity and optical flow partitioning based on the brightness invariance assumption. We investigate new variational approaches to these problems with Potts priors and possibly box constraints. For the optical flow partitioning, our model includes vector-valued data and an adapted Potts regularizer. Using the notation of asymptotically level stable functions we prove the existence of global minimizers of our functionals. We propose a modified alternating direction method of minimizers. This iterative algorithm requires the computation of global minimizers of classical univariate Potts problems which can be done efficiently by dynamic programming. We prove that the algorithm converges both for the constrained and unconstrained problems. Numerical examples demonstrate the very good performance of our partitioning method

    Disparity map generation based on trapezoidal camera architecture for multiview video

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    Visual content acquisition is a strategic functional block of any visual system. Despite its wide possibilities, the arrangement of cameras for the acquisition of good quality visual content for use in multi-view video remains a huge challenge. This paper presents the mathematical description of trapezoidal camera architecture and relationships which facilitate the determination of camera position for visual content acquisition in multi-view video, and depth map generation. The strong point of Trapezoidal Camera Architecture is that it allows for adaptive camera topology by which points within the scene, especially the occluded ones can be optically and geometrically viewed from several different viewpoints either on the edge of the trapezoid or inside it. The concept of maximum independent set, trapezoid characteristics, and the fact that the positions of cameras (with the exception of few) differ in their vertical coordinate description could very well be used to address the issue of occlusion which continues to be a major problem in computer vision with regards to the generation of depth map

    Nilpotent Approximations of Sub-Riemannian Distances for Fast Perceptual Grouping of Blood Vessels in 2D and 3D

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    We propose an efficient approach for the grouping of local orientations (points on vessels) via nilpotent approximations of sub-Riemannian distances in the 2D and 3D roto-translation groups SE(2)SE(2) and SE(3)SE(3). In our distance approximations we consider homogeneous norms on nilpotent groups that locally approximate SE(n)SE(n), and which are obtained via the exponential and logarithmic map on SE(n)SE(n). In a qualitative validation we show that the norms provide accurate approximations of the true sub-Riemannian distances, and we discuss their relations to the fundamental solution of the sub-Laplacian on SE(n)SE(n). The quantitative experiments further confirm the accuracy of the approximations. Quantitative results are obtained by evaluating perceptual grouping performance of retinal blood vessels in 2D images and curves in challenging 3D synthetic volumes. The results show that 1) sub-Riemannian geometry is essential in achieving top performance and 2) that grouping via the fast analytic approximations performs almost equally, or better, than data-adaptive fast marching approaches on Rn\mathbb{R}^n and SE(n)SE(n).Comment: 18 pages, 9 figures, 3 tables, in review at JMI
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