What is computed by structure from motion algorithms?

  • Cornelia Fermüller
  • Yiannis Aloimonos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1406)


In the literature we find two classes of algorithms which, on the basis of two views of a scene, recover the rigid transformation between the views and subsequently the structure of the scene. The first class contains techniques which require knowledge of the correspondence or the motion field between the images and are based on the epipolar constraint. The second class contains so-called direct algorithms which require knowledge about the value of the flow in one direction only and are based on the positive depth constraint. Algorithms in the first class achieve the solution by minimizing a function representing deviation from the epipolar constraint while direct algorithms find the 3D motion that, when used to estimate depth, produces a minimum number of negative depth values. This paper presents a stability analysis of both classes of algorithms. The formulation is such that it allows comparison of the robustness of algorithms in the two classes as well as within each class. Specifically, a general statistical model is employed to express the functions which measure the deviation from the epipolar constraint and the number of negative depth values, and these functions are studied with regard to their topographic structure, specifically as regards the errors in the 3D motion parameters at the places representing the minima of the functions. The analysis shows that for algorithms in both classes which estimate all motion parameters simultaneously, the obtained solution has an error such that the projections of the translational and rotational errors on the image plane are perpendicular to each other. Furthermore, the estimated projection of the translation on the image lies on a line through the origin and the projection of the real translation.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Cornelia Fermüller
    • 1
  • Yiannis Aloimonos
    • 1
  1. 1.Computer Vision Laboratory, Center for Automation ResearchUniversity of MarylandCollege ParkUSA

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