GMCC is introduced as a linear-transformation-invariant similarity measure for trajectories, extending the multiple correlation coefficient for use in imitation learning.
Time Warp Edit Distance
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
This technical report details a family of time warp distances on the set of discrete time series. This family is constructed as an editing distance whose elementary operations apply on linear segments. A specific parameter allows controlling the stiffness of the elastic matching. It is well suited for the processing of event data for which each data sample is associated with a timestamp, not necessarily obtained according to a constant sampling rate. Some properties verified by these distances are proposed and proved in this report.
fields
cs.HC 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Generalized Multiple Correlation Coefficient as a Similarity Measurements between Trajectories
GMCC is introduced as a linear-transformation-invariant similarity measure for trajectories, extending the multiple correlation coefficient for use in imitation learning.