On hidden Markov models and cyclic strings for shape recognition

作者：

Highlights：

• Starting point invariance in contour classification is not achieved with current HMM proposals.

• Cyclic strings are adequate for achieving starting point invariance.

• We modify the Baum–Welch and Viterbi algorithms for dealing with cyclic strings.

• A new model, cyclic linear HMMs, speeds up training and classification of cyclic strings.

• Our experiments show that our proposals outperform other methods in the literature.

摘要

Highlights•Starting point invariance in contour classification is not achieved with current HMM proposals.•Cyclic strings are adequate for achieving starting point invariance.•We modify the Baum–Welch and Viterbi algorithms for dealing with cyclic strings.•A new model, cyclic linear HMMs, speeds up training and classification of cyclic strings.•Our experiments show that our proposals outperform other methods in the literature.

论文关键词：Hidden Markov models,Cyclic strings,Shape recognition

论文评审过程：Received 28 May 2013, Revised 19 November 2013, Accepted 29 January 2014, Available online 8 February 2014.

论文官网地址：https://doi.org/10.1016/j.patcog.2014.01.018