אסיף מאגר המחקר החקלאי

Analyzing movement trajectories using a Markov bi-clustering method

Year:

2009

Source of publication :

Authors :

Volume :

27

Co-Authors:

Erez, K., The Gonda Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
Goldberger, J., School of Engineering, Bar-Ilan University, Ramat-Gan 52900, Israel
Sosnik, R., The Gonda Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
Shemesh, M., The Gonda Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
Rothstein, S., The Gonda Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
Abeles, M., The Gonda Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel

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Abstract:

In this study we treat scribbling motion as a compositional system in which a limited set of elementary strokes are capable of concatenating amongst themselves in an endless number of combinations, thus producing an unlimited repertoire of complex constructs. We broke the continuous scribblings into small units and then calculated the Markovian transition matrix between the trajectory clusters. The Markov states are grouped in a way that minimizes the loss of mutual information between adjacent strokes. The grouping algorithm is based on a novel markov-state bi-clustering algorithm derived from the Information-Bottleneck principle. This approach hierarchically decomposes scribblings into increasingly finer elements. We illustrate the usefulness of this approach by applying it to human scribbling. © Springer Science+Business Media, LLC 2009.

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