'Dynamism of A Dog on A Leash' Or Behavior Classification By Eigen-Decomposition of Periodic Motions

Roman Goldenberg, Ron Kimmel, Ehud Rivlin, and Michael Rudzsky.
'Dynamism of a Dog on a Leash' or Behavior Classification by Eigen-Decomposition of Periodic Motions.
In ECCV (1), 461-475, 2002

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Abstract

Following Futurism, we show how periodic motions can be represented by a small number of eigen-shapes that capture the whole dynamic mechanism of periodic motions. Spectral decomposition of a silhouette of an object in motion serves as a basis for behavior classification by principle component analysis. The boundary contour of the walking dog, for example, is first computed efficiently and accurately. After normalization, the implicit representation of a sequence of silhouette contours given by their corresponding binary images, is used for generating eigen-shapes for the given motion. Singular value decomposition produces these eigen-shapes that are then used to analyze the sequence. We show examples of object as well as behavior classification based on the eigen-decomposition of the binary silhouette sequence.

Co-authors

Bibtex Entry

@inproceedings{GoldenbergKRR02i,
  title = {'Dynamism of a Dog on a Leash' or Behavior Classification by Eigen-Decomposition of Periodic Motions.},
  author = {Roman Goldenberg and Ron Kimmel and Ehud Rivlin and Michael Rudzsky},
  year = {2002},
  booktitle = {ECCV (1)},
  pages = {461-475},
  abstract = {Following Futurism, we show how periodic motions can be represented by a small number of eigen-shapes that capture the whole dynamic mechanism of periodic motions. Spectral decomposition of a silhouette of an object in motion serves as a basis for behavior classification by principle component analysis. The boundary contour of the walking dog, for example, is first computed efficiently and accurately. After normalization, the implicit representation of a sequence of silhouette contours given by their corresponding binary images, is used for generating eigen-shapes for the given motion. Singular value decomposition produces these eigen-shapes that are then used to analyze the sequence. We show examples of object as well as behavior classification based on the eigen-decomposition of the binary silhouette sequence.}
}