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David H. Marimont

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

2 papers
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2

ICRA Conference 1994 Conference Paper

Geometric Methods for Relative Reconstruction from Weakly Calibrated Images

  • Jean Ponce
  • David H. Marimont
  • Todd A. Cass

We present several new geometric methods for relative stereo and motion reconstruction using a discrete set of point correspondences. We suppose that the epipoles are known but do not assume any knowledge of the cameras' intrinsic or extrinsic parameters. In each case, we choose a set of five points as a basis for projective space and perform reconstruction relative to these five points. We also present a new technique for reprojection without reconstruction. We have implemented the proposed methods and present several examples using real images. >

AAAI Conference 1984 Conference Paper

A Representation for Image Curves

  • David H. Marimont

A representation for image curves and an algorithm for its computation are introduced. The representation is designed to facilitate matching of image curves to completely specified model plane curves and estimation of their orientation in space, despite the presence of noise. variable resolution, or partial occlusion. This is an important subproblem of model-based vision. A curve may be represented at a variety of scales, and a strategy for selecting natural scales is proposed. At each scale, the representaion is simply a list of positions in the plane, with tangent directions and curvatures specified at each position; each curvature is either a zero or an extremum (hereafter critical points). The algorithm for computing the representation involves smoothing with gaussians at different scales: extracting tile critical points from the smoothed curves. and using dynamic programming to construct a list of critical points which best approximate the curve for each length of list possible. We propose to examine the tradeoff between the error of the approximation and length of the lists to find natural scales.

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