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Sökning: WFRF:(Perd'och Michal)

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1.
  • Cornelius, Hugo, et al. (författare)
  • Efficient symmetry detection using local affine frames
  • 2007
  • Ingår i: Image Analysis, Proceedings. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783540730392 ; , s. 152-161
  • Konferensbidrag (refereegranskat)abstract
    • We present an efficient method for detecting planar bilateral symmetries under perspective projection. The method uses local affine frames (LAFs) constructed on maximally stable extremal regions or any other affine covariant regions detected in the image to dramatically improve the process of detecting symmetric objects under perspective distortion. In contrast to the previous work no Hough transform, is used. Instead, each symmetric pair of LAFs votes just once for a single axis of symmetry. The time complexity of the method is n log(n), where n is the number of LAFs, allowing a near real-time performance. The proposed method is robust to background clutter and partial occlusion and is capable of detecting an arbitrary number of symmetries in the image.
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2.
  • Lochman, Yaroslava, 1996, et al. (författare)
  • BabelCalib: A Universal Approach to Calibrating Central Cameras
  • 2021
  • Ingår i: Proceedings of the IEEE International Conference on Computer Vision. - 1550-5499. ; , s. 15233-15242
  • Konferensbidrag (refereegranskat)abstract
    • Existing calibration methods occasionally fail for large field-of-view cameras due to the non-linearity of the underlying problem and the lack of good initial values for all parameters of the used camera model. This might occur because a simpler projection model is assumed in an initial step, or a poor initial guess for the internal parameters is pre-defined. A lot of the difficulties of general camera calibration lie in the use of a forward projection model. We side-step these challenges by first proposing a solver to calibrate the parameters in terms of a back-projection model and then regress the parameters for a target forward model. These steps are incorporated in a robust estimation framework to cope with outlying detections. Extensive experiments demonstrate that our approach is very reliable and returns the most accurate calibration parameters as measured on the downstream task of absolute pose estimation on test sets. The code is released at https://github.com/ylochman/babelcalib.
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