Title
Self-organizing trajectories.
Abstract
DBA results in oscillating curves if the number of nodes is high.Self-organizing trajectories produce high-quality trajectory averages.Exponential averaging allows real-time estimation of trajectory variance. Trajectories and parameterized curves are data types of growing importance. Many measures for such data have been proposed in order to provide analogues to the mean and variance of vectors. We identify a counterintuitive oscillating behavior of dynamic time warp-based averages on certain data sets. We present an algorithm that combines ideas from both self-organizing maps and dynamic time warping that avoids these oscillations and hence promises more representative curve averages. These improvements also allow for accurate estimation of the piece-wise variance for a set of general N-dimensional trajectories. The run-time performance is demonstrated on movement data from rowing, where we are able to provide performance feedback in real-time to users in a simulator.
Year
DOI
Venue
2016
10.1016/j.patrec.2016.09.012
Pattern Recognition Letters
DocType
Volume
Issue
Journal
84
C
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Leonard Johard1114.91
Emanuele Ruffaldi226138.28