Bag of Class Posteriors, a new multivariate time series classifier applied to animal behaviour identification

作者：

Highlights：

• A new multi-scale time series classifier is proposed using class posterior estimates.

• The classifier infers a large set of animal behaviour using motion based time series.

• The proposed classifier outperforms benchmark classifiers by between 43% and 77%.

• The proposed classifier is found to be more efficient than the Bag of Features model.

摘要

•A new multi-scale time series classifier is proposed using class posterior estimates.•The classifier infers a large set of animal behaviour using motion based time series.•The proposed classifier outperforms benchmark classifiers by between 43% and 77%.•The proposed classifier is found to be more efficient than the Bag of Features model.

论文关键词：Time series classification,Class posterior estimates,Precision cattle management,Inertial Measurement Units

论文评审过程：Available online 19 December 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.11.033