NLP应用中注视方向的自动检测

Ruxandra Vrânceanu, C. Florea, L. Florea, C. Vertan
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引用次数: 3

摘要

本文提出了一种基于眼睛中心在眼睛边界框内的位置来检测神经语言编程中使用的Eye access Cue (EAC)模型的解决方案。使用基于等影点曲率的虹膜中心检测方法和基于图模型的面部点检测方法确定眼点。对边界框内的亮度分布进行分析,并增加一个额外的特征来提高检测率。本文还介绍了一个带有手动标记的新数据库,用于测试由各种分类器生成的EAC检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic detection of gaze direction for NLP applications
This paper proposes a solution for detecting the Eye Accessing Cue (EAC) model used in Neuro-Linguistic Programming based on the position of the eye center inside the bounding box of the eye. The eye points are determined using an iris center detection method based on the curvature of the isophote and a facial points detection method based on graph models. The distribution of luminance is analyzed inside the bounding box and added as an extra feature to increase the detection rate. This paper also introduces a new database with manual markings used for testing the EAC detection as generated by various classifiers.
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