Hybrid classifier based human activity recognition using the silhouette and cells

作者：

Highlights：

• A new approach for the recognition of human activity using silhouette is proposed.

• The effectiveness of the proposed approach is measured using various classifiers.

• A new hybrid classification model is proposed to boost the recognition accuracy.

• The minimum classification error is achieved through a hybrid classification model.

摘要

•A new approach for the recognition of human activity using silhouette is proposed.•The effectiveness of the proposed approach is measured using various classifiers.•A new hybrid classification model is proposed to boost the recognition accuracy.•The minimum classification error is achieved through a hybrid classification model.

论文关键词：Human activity recognition (HAR),Linear Discriminant Analysis,K-Nearest Neighbor,Support Vector Machine,Hybrid classifier

论文评审过程：Available online 7 May 2015, Version of Record 31 May 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.04.039