Hand gesture recognition via enhanced densely connected convolutional neural network

作者：

Highlights：

• A taxonomy of vision-based hand gesture recognition in the literature is presented.

• Model customization and data augmentation are explored to improve generalization.

• Ablation study for the proposed model has been conducted.

• Performance of the proposed model is evaluated on several hand gesture datasets.

摘要

•A taxonomy of vision-based hand gesture recognition in the literature is presented.•Model customization and data augmentation are explored to improve generalization.•Ablation study for the proposed model has been conducted.•Performance of the proposed model is evaluated on several hand gesture datasets.

论文关键词：Sign language recognition,Hand gesture recognition,Convolutional neural network (CNN),Enhanced densely connected convolutional neural network (EDenseNet)

论文评审过程：Received 10 November 2020, Revised 18 February 2021, Accepted 25 February 2021, Available online 4 March 2021, Version of Record 24 March 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114797