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Communication Dans Un Congrès Année : 2018

Self-Calibrating Isometric Non-Rigid Structure-from-Motion

Adrien Bartoli
  • Fonction : Auteur
Daniel Pizarro
  • Fonction : Auteur

Résumé

We present self-calibrating isometric non-rigid structurefrom-motion (SCIso-NRSfM), the first method to reconstruct a non-rigid object from at least three monocular images with constant but unknown focal length. The majority of NRSfM methods using the perspective camera simply assume that the calibration is known. SCIso-NRSfM leverages the recent powerful differential approaches to NRSfM, based on formulating local polynomial constraints, where local means correspondencewise. In NRSfM, the local shape may be solved from these constraints. In SCIso-NRSfM, the difficulty is to also solve for the focal length as a global variable. We propose to eliminate the shape using resultants, obtaining univariate polynomials for the focal length only, whose sum of squares can then be globally minimized. SCIso-NRSfM thus solves for the focal length by integrating the constraints for all correspondences and the whole image set. Once this is done, the local shape is easily recovered. Our experiments show that its performance is very close to the state-of-the-art methods that use a calibrated camera.
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Dates et versions

hal-04391622 , version 1 (12-01-2024)

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  • HAL Id : hal-04391622 , version 1

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Shaifali Parashar, Adrien Bartoli, Daniel Pizarro. Self-Calibrating Isometric Non-Rigid Structure-from-Motion. ECCV, 2018, Munich, Germany. ⟨hal-04391622⟩
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