The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

Current approaches for detecting periodic motion assume a stationary camera and place limits on an object's motion. These approaches rely on the assumption that a periodic motion projects to a set of periodic image curves, an assumption that is invalid in general. Using affine-invariance, we derive necessary and sufficient conditions for an image sequence to be the projection of a periodic motion. No restrictions are placed on either the motion of the camera or the object. Our algorithm is shown to be provably-correct for noise-free data and is extended to be robust with respect to occlusions and noise. The extended algorithm is evaluated with real and synthetic image sequences.

Notes

Text Reference

Steven Seitz and C. R. Dyer, "Affine Invariant Detection of Periodic Motion," Proc. Computer Vision and Pattern Recognition Conference (CVPR '94), 1994, pp. 970 - 975.

BibTeX Reference

@inproceedings{Seitz_1994_2851,
   author = "Steven Seitz and C. R. Dyer",
   title = "Affine Invariant Detection of Periodic Motion",
   booktitle = "Proc. Computer Vision and Pattern Recognition Conference (CVPR '94)",
   pages = "970 - 975",
   year = "1994",
}

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