Visual Quasi-Periodicity E. Pogalin, A. W. M. Smeulders, A. H. C. Thean In IEEE Conference on Computer Vision and Pattern Recognition 2008. [bibtex] [pdf] [url]

Periodicity is at the core of the recognition of many actions. This paper takes the following steps to detect and measure periodicity. 1) We establish a conceptual framework of classifying periodicity in 10 essential cases, the most important of which are flashing (of a traffic light), pulsing (of an anemone), swinging (of wings), spinning (of a swimmer), turning (of a conductor), shuttling (of a brush), drifting (of an escalator) and thrusting (of a kangaroo). 2) We present an algorithm to detect all cases by the one and the same algorithm. It tracks the object independent of the object's appearance, then performs probabilistic PCA and spectral analysis followed by detection and frequency measurement. The method shows good performance with fixed parameters for examples of all above cases assembled from the Internet. 3) Application of the method, completely unaltered, to a random half hour of CNN news has led to an 80% score.



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@InProceedings{PogalinCVPR2008,
  author       = "Pogalin, E. and Smeulders, A. W. M. and Thean, A. H. C.",
  title        = "Visual Quasi-Periodicity",
  booktitle    = "IEEE Conference on Computer Vision and Pattern Recognition",
  year         = "2008",
  url          = "https://ivi.fnwi.uva.nl/isis/publications/2008/PogalinCVPR2008",
  pdf          = "https://ivi.fnwi.uva.nl/isis/publications/2008/PogalinCVPR2008/PogalinCVPR2008.pdf",
  has_image    = 1
}