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Revisiting Single-View Shape Tensors: Theory and Applications

  • Anat Levin
  • Amnon Shashua
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2351)

Abstract

Given the projection of a sufficient number of points it is possible to algebraically eliminate the camera parameters and obtain view-invariant functions of image coordinates and space coordinates. These single view invariants have been introduced in the past, however, they are not as well understood as their dual multi-view tensors. In this paper we revisit the dual tensors (bilinear, trilinear and quadlinear), both the general and the reference-plane reduced version, and describe the complete set of synthetic constraints, properties of the tensor slices, reprojection equations, non-linear constraints and reconstruction formulas. We then apply some of the new results, such as the dual reprojection equations, for multi-view point tracking under occlusions.

Keywords

Linear Constraint Projection Matrice Reconstruction Formula Homography Matrix Trifocal Tensor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Anat Levin
    • 1
  • Amnon Shashua
    • 1
  1. 1.School of Computer Science and EngineeringThe Hebrew UniversityJerusalemIsrael

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