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Feature Trajectory Retrieval with Application to
Accurate Structure and Motion Recovery

7th International Symposium on Visual Computing (ISVC 2011)

Short Abstract

Two Extensions to common Structure and Motion Recovery approach:
  1. Feature Trajectory Retrieval (FTR)
  2. increases reliability
  3. Gaussian Gradient Approximation in SIFT subpel feature localization
  4. increases accuracy

Results

  • the video shows a visual comparison of the estimated camera paths with integrated virtual objects [1]
    1. input sequence
    2. reference SIFT features and frame to frame correspondences only
    3. reference SIFT features and Feature Trajectory Retrieval (FTR)
    4. Gaussian Gradient Approximation (Gaussian SIFT) and FTR
  • for an objective evaluation see paper / presentation slides
  • the combined method - Gaussian SIFT and FTR - provides best results with minimal drift
  • Paper

    [1] Kai Cordes, Oliver Müller, Bodo Rosenhahn, and Jörn Ostermann: Feature Trajectory Retrieval with Application to Accurate Structure and Motion Recovery, Advances in Visual Computing, 7th International Symposium (ISVC), Springer, LNCS 6938, pp. 156--167, 2011
  • ISVC11-Cordes_FTR-SAM.pdf
  • Presentation

  • ISVC2011-pres.pdf
  • High Quality Video (720x576, 19 MB)

  • ISVC2011.avi
  • Models

  • Snoopy (.obj)
  • Woodstock (.obj)