DeepSafeDrive: A grammar-aware driver parsing approach to Driver Behavioral Situational Awareness (DB-SAW)

作者：

Highlights：

• Incorporate grammatical structure telling the relationship between parts into CNNs.

• Propose a fast and effective segmentation using prior knowledge of deep probability map to define within-subgraph and between-subgraph.

• The deep features capable of representing both information of feature and shape.

• To the best of our knowledge, this is the first time an automatic system to support Driver Behavioral Situational Awareness (DB-SAW) has been presented. Particularly, it is the first system that finds the parts of the driver, i.e. head, body, seat belt, hands, eyes, mouth and nose.

摘要

Highlights•Incorporate grammatical structure telling the relationship between parts into CNNs.•Propose a fast and effective segmentation using prior knowledge of deep probability map to define within-subgraph and between-subgraph.•The deep features capable of representing both information of feature and shape.•To the best of our knowledge, this is the first time an automatic system to support Driver Behavioral Situational Awareness (DB-SAW) has been presented. Particularly, it is the first system that finds the parts of the driver, i.e. head, body, seat belt, hands, eyes, mouth and nose.

论文关键词：Driver parsing,Pictorial structure,Deep features,Region with Convolutional Neural Networks (R-CNN),Structure based N-cuts

论文评审过程：Received 16 February 2016, Revised 28 November 2016, Accepted 29 November 2016, Available online 2 December 2016, Version of Record 12 March 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.11.028