A Markov clustering method for analyzing movement trajectories

Jacob Goldberger; Keren Erez; Moshe Abeles

doi:10.1109/mlsp.2007.4414308

A Markov clustering method for analyzing movement trajectories

Jacob Goldberger
, Keren Erez
, Moshe Abeles

Bar-Ilan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

In this study we analyze monkeys' hand movement; our strategy is compositional, division of complex movement into basic simple components-primitives. Representing each trajectory segment as vectors of directions, we model the movement trajectory as a large Markov process where each state is related with an average trajectory pattern. In the next step, in order to find the movements primitives, we cluster the Markov states according to their probabilistic similarity. We present an information theoretic co-clustering algorithm which can be interpreted as a block-matrix approximation of the Markov transition matrix. The performance of the suggested approach is demonstrated on real recorded data.

Original language	English
Title of host publication	Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP
Publisher	IEEE Computer Society
Pages	211-216
Number of pages	6
ISBN (Print)	1424415667, 9781424415663
DOIs	https://doi.org/10.1109/mlsp.2007.4414308
State	Published - 2007
Event	17th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2007 - Thessaloniki, Greece Duration: 27 Aug 2007 → 29 Aug 2007

Publication series

Name	Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP

Conference

Conference	17th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2007
Country/Territory	Greece
City	Thessaloniki
Period	27/08/07 → 29/08/07

Access to Document

10.1109/mlsp.2007.4414308

Cite this

Goldberger, J., Erez, K., & Abeles, M. (2007). A Markov clustering method for analyzing movement trajectories. In Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP (pp. 211-216). Article 4414308 (Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP). IEEE Computer Society. https://doi.org/10.1109/mlsp.2007.4414308

Goldberger, Jacob ; Erez, Keren ; Abeles, Moshe. / A Markov clustering method for analyzing movement trajectories. Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP. IEEE Computer Society, 2007. pp. 211-216 (Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP).

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title = "A Markov clustering method for analyzing movement trajectories",

abstract = "In this study we analyze monkeys' hand movement; our strategy is compositional, division of complex movement into basic simple components-primitives. Representing each trajectory segment as vectors of directions, we model the movement trajectory as a large Markov process where each state is related with an average trajectory pattern. In the next step, in order to find the movements primitives, we cluster the Markov states according to their probabilistic similarity. We present an information theoretic co-clustering algorithm which can be interpreted as a block-matrix approximation of the Markov transition matrix. The performance of the suggested approach is demonstrated on real recorded data.",

author = "Jacob Goldberger and Keren Erez and Moshe Abeles",

year = "2007",

doi = "10.1109/mlsp.2007.4414308",

language = "אנגלית",

isbn = "1424415667",

series = "Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP",

publisher = "IEEE Computer Society",

pages = "211--216",

booktitle = "Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP",

address = "ארצות הברית",

note = "17th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2007 ; Conference date: 27-08-2007 Through 29-08-2007",

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Goldberger, J, Erez, K & Abeles, M 2007, A Markov clustering method for analyzing movement trajectories. in Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP., 4414308, Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP, IEEE Computer Society, pp. 211-216, 17th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2007, Thessaloniki, Greece, 27/08/07. https://doi.org/10.1109/mlsp.2007.4414308

A Markov clustering method for analyzing movement trajectories. / Goldberger, Jacob; Erez, Keren; Abeles, Moshe.
Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP. IEEE Computer Society, 2007. p. 211-216 4414308 (Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Goldberger J, Erez K, Abeles M. A Markov clustering method for analyzing movement trajectories. In Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP. IEEE Computer Society. 2007. p. 211-216. 4414308. (Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP). doi: 10.1109/mlsp.2007.4414308

A Markov clustering method for analyzing movement trajectories

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