基于驾驶员视频的光适应人脸配准

Zuojin Li, Jun Peng, Liukui Chen, S. S. Tirumala
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引用次数: 1

摘要

在真实驾驶条件下,基于驾驶员视频的疲劳监测系统受光照环境影响较大,不利于人脸信息的配准,进而影响监控的准确性。本文在基于主动外观模型的人脸配准方法的基础上,分析了光照条件变化导致人脸配准失效的原因,提出了一种改进的主动外观模型配准算法。实验表明,改进的AAM方法可以在变化的光照环境下很好地对驾驶员面部进行配准,从而提高了基于驾驶员视频的疲劳状态识别的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Light-adaptive face registration based on drivers' video
Under real driving conditions, the fatigue monitoring system based on drivers' video is highly affected by light environment, which deteriorates the registration of facial information and thus the accuracy of surveillance. This paper, on the basis of AAM (Active Appearance Model)-based face registration method, analyzes the reasons of its failure when lighting conditions change and proposes an improved AAM algorithm. The experiments show that the improved AAM method can well register driver's face under changing lighting environment, and thus improve the accuracy in fatigue state recognition based on drivers' videos.
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