Towards a driver's gaze zone classifier using a single camera robust to temporal and permanent face occlusions

研究成果: Conference contribution

抄録

Although exists several drivers' gaze direction classifiers to prevent traffic accidents caused by inattentive driving, making this classification while the driver's face is temporarily or permanently occluded remains exceptionally challenging. For example, drivers using masks, sunglasses, or scarves and daily light variations are non-ideal conditions that recurrently appear in an everyday driving scenario and are frequently overlooked by the existing classifiers. This paper presents a single camera framework gaze zone classifier that operates robustly even during non-uniform lighting, non-frontal face pose, and faces undergo temporal or permanent occlusions. The usage of a normalized dense aligned face pose vector, the classification result of a pre-processed right eye area pixels, and the classification result of a pre-processed left eye area pixels is the cornerstone of the feature vector used in our model. The key of this paper is double-folded: firstly, the usage of a normalized dense alignment for a robust face, landmark, and head-pose direction detection and secondly, the processing of the right and left eye images using computer vision and deep learning techniques for refining, modifying, and finally labeling eyes information. Experiments on a challenging dataset involving non-uniform lighting, non-frontal face pose, and faces with temporal or permanent occlusions show each feature's importance towards making a robust gaze zone classifier under unconstrained driving situations.

本文言語English
ホスト出版物のタイトル32nd IEEE Intelligent Vehicles Symposium, IV 2021
出版社Institute of Electrical and Electronics Engineers Inc.
ページ578-585
ページ数8
ISBN(電子版)9781728153940
DOI
出版ステータスPublished - 2021 7 11
イベント32nd IEEE Intelligent Vehicles Symposium, IV 2021 - Nagoya, Japan
継続期間: 2021 7 112021 7 17

出版物シリーズ

名前IEEE Intelligent Vehicles Symposium, Proceedings
2021-July

Conference

Conference32nd IEEE Intelligent Vehicles Symposium, IV 2021
国/地域Japan
CityNagoya
Period21/7/1121/7/17

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 自動車工学
  • モデリングとシミュレーション

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