A Robust Driver's Gaze Zone Classification using a Single Camera for Self-occlusions and Non-aligned Head and Eyes Direction Driving Situations

Catherine Lollett, Hiroaki Hayashi, Mitsuhiro Kamezaki, Shigeki Sugano

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Distracted driving is one of the most common causes of traffic accidents around the world. Recognizing the driver's gaze direction during a maneuver could be an essential step for avoiding the matter mentioned above. Thus, we propose a gaze zone classification system that serves as a base of supporting systems for driver's situation awareness. However, the challenge is to estimate the driver's gaze inside not ideal scenarios, specifically in this work, scenarios where may occur self-occlusions or non-aligned head and eyes direction of the driver. Firstly, towards solving miss classifications during self-occlusions scenarios, we designed a novel protocol where a 3D full facial geometry reconstruction of the driver from a single 2D image is made using the state-of-the-art method PRNet. To solve the miss classification when the driver's head and eyes direction are not aligned, eyes and head information are extracted. After this, based on a mix of different data pre-processing and deep learning methods, we achieved a robust classifier in situations where self-occlusions or non-aligned head and eyes direction of the driver occur. Our results from the experiments explicitly measure and show that the proposed method can make an accurate classification for the two before-mentioned problems. Moreover, we demonstrate that our model generalizes new drivers while being a portable and extensible system, making it easy-adaptable for various automobiles.

本文言語English
ホスト出版物のタイトル2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ4302-4308
ページ数7
ISBN(電子版)9781728185262
DOI
出版ステータスPublished - 2020 10月 11
イベント2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020 - Toronto, Canada
継続期間: 2020 10月 112020 10月 14

出版物シリーズ

名前Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
2020-October
ISSN(印刷版)1062-922X

Conference

Conference2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020
国/地域Canada
CityToronto
Period20/10/1120/10/14

ASJC Scopus subject areas

  • 電子工学および電気工学
  • 制御およびシステム工学
  • 人間とコンピュータの相互作用

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