TY - GEN
T1 - A Markov clustering method for analyzing movement trajectories
AU - Goldberger, Jacob
AU - Erez, Keren
AU - Abeles, Moshe
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=48149093658&partnerID=8YFLogxK
U2 - 10.1109/MLSP.2007.4414308
DO - 10.1109/MLSP.2007.4414308
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AN - SCOPUS:48149093658
SN - 1424415667
SN - 9781424415663
T3 - Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP
SP - 211
EP - 216
BT - Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP
T2 - 17th IEEE International Workshop on Machine Learning for Signal Processing, MLSP-2007
Y2 - 27 August 2007 through 29 August 2007
ER -