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Projective Reconstruction for SaM from Image Sequence

Projective Reconstruction for SaM from Image Sequence. Key Frame Selection(1). Error Function Reprojection error IAC(Image of Absolute Conic). Key Frame Selection(2). Simon’s Method. IAC error graph. IAC error accumulation graph. Key Frame Selection(3). Nister’s Method. IAC error graph.

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Projective Reconstruction for SaM from Image Sequence

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  1. Projective Reconstruction for SaM from Image Sequence

  2. Key Frame Selection(1) • Error Function • Reprojection error • IAC(Image of Absolute Conic)

  3. Key Frame Selection(2) • Simon’s Method IAC error graph IAC error accumulation graph

  4. Key Frame Selection(3) • Nister’s Method IAC error graph IAC error accumulation graph

  5. Reference Automatic camera recovery for closed or open image sequences. - A. Fitzgibbon and A. Zisserman. - ECCV1998, pages 311–326. Springer-Verlag, June 1998.

  6. From triplets to sub-frame • Registration of image triplets to sub-sequence • The goal is to obtain a common set of 3D points and a camera for each view, such that the reprojection error • Registration will proceed in two steps • 3D Transformation of projective frames • Bundle adjustment

  7. Correspondence by simultaneously estimating F P1 P2 P3 P4 P5 P6 T456 T123 3D structure from T123 3D structure from T456 Projective Transformation Merging Method-I • Direct 3D point registration

  8. T123 P3 P1 P2 P’5 P’3 P’4 T345 Merging Method-II • Enforcing camera consistency : one-view overlap Algebraic distance case Euclidean distance case nonlinear minimization over v is required

  9. Maximizing camera consistency : Two-view overlap H : DOF 15, P : DOF 11 T123 P1 P2 P3 P’3 P’2 P’4 T234 Merging Method-III

  10. Correspondence by simultaneously estimating F P1 P2 P3 P4 P5 P6 T456 T123 Transformation ?? Merging by error function • Merging by reprojection error minimum.

  11. Further Work • Bundle adjustment • Estimation of Absolute quardric based LMedS.

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