在区域分割支持的注视感知环境下实现更好的驾驶

Proceeedings of the 19th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2022) Pub Date : 2022-11-08 DOI:10.33965/celda2022_202207l007

Taketo Yamada, Kenji Matsuura, Hironori Takeuchi, Akihiro Kashihara, Kenichi Yamasaki, Genta Kurita

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引用次数: 1

摘要

重要的是要使汽车司机提高他们寻找识别关键物体或区域的精确方式。本研究设计了一个系统，该系统遵循这样的动机，以重要性权重区分显示器中的几个区域。目前提出的一个成功的区域检测功能为司机提供了一个与专家比较他们的目光的机会。具体实现方法包括U-Net，这是机器学习与网格分割相结合的主要技术之一。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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TOWARD BETTER DRIVING WITH GAZE AWARENESS ENVIRONMENT SUPPORTED BY AREA SEGMENTATION

It is important to make car-drivers improve their way of looking for recognizing key objects or areas precisely. This study designs a system following such a motivation that distinguishes several areas in a display with weights of importance. A present proposing function for successful area detection offers drivers an opportunity to compare their gaze with experts. Concrete method for this implementation includes U-Net that is one of major techniques of machine learning combined with grid segmentation.

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Proceeedings of the 19th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2022)

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