Jump to content

Self-similarity matrix

From Wikipedia, the free encyclopedia

This is an old revision of this page, as edited by Monkbot (talk | contribs) at 08:44, 24 July 2014 (Definition: Task 5: Fix CS1 deprecated coauthor parameter errors). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

In data analysis, the self-similarity matrix is a graphical representation of similar sequences in a data series.

Similarity can be explained by different measures, like spatial distance (distance matrix), correlation, or comparison of local histograms or spectral properties (e.g. IXEGRAM[1]). This technique is also applied for the search of a given pattern in a long data series as in gene matching.[citation needed] A similarity plot can be the starting point for dot plots or recurrence plots.

Definition

To construct a self-similarity matrix, one first transforms a data series into an ordered sequences of feature vectors , where each vector describes the relevant features of a data series in a given local interval. Then the self-similarity matrix is formed by computing the similarity of pairs of feature vectors

where is a function measuring the similarity of the two vectors, for instance, the inner product . Then similar segments of feature vectors will show up as path of high similarity along diagonals of the matrix.[2]

Example

Similarity plot, a variant of recurrence plot, obtained for different views of human actions are shown to produce similar patterns.[3]

See also

References

  1. ^ M. A. Casey; A. Westner (July -00 2000). "Separation of mixed audio sources by independent subspace analysis" (PDF). Proc. Int. Comput. Music Conf. Retrieved 2013-11-19. {{cite journal}}: Check date values in: |date= (help)
  2. ^ Müller, Meinard; Michael Clausen (2007). "Transposition-invariant self-similarity matrices" (PDF). Proceedings of the 8th International Conference on Music Information Retrieval (ISMIR 2007): 47–50. Retrieved 2013-11-19.
  3. ^ I.N. Junejo, E. Dexter, I. Laptev, Patrick Pérez (2008). "Cross-View Action Recognition from Temporal Self-Similarities". In Proc. European Conference on Computer Vision (ECCV), Marseille, France. doi:10.1007/978-3-540-88688-4_22.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • J. Foote (1999). "Visualizing Music and Audio using Self-Similarity". In: Proceedings of ACM Multimedia '99, Orlando, Florida. doi:10.1145/319463.319472.
  • M. A. Casey (2002). "Sound Classification and Similarity Tools". Introduction to MPEG-7: Multimedia Content Description Language. J. Wiley: 309–323. ISBN 978-0471486787. {{cite journal}}: Unknown parameter |editors= ignored (|editor= suggested) (help)