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Estimating Point of Regard with a Consumer Camera at a Distance

机译:远距离使用消费类相机估算问候点

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In this work, we have studied the viability of a novel technique to estimate the POR that only requires video feed from a consumer camera. The system can work under uncontrolled light conditions and does not require any complex hardware setup. To that end we propose a system that uses PCA feature extraction from the eyes region followed by non-linear regression. We evaluated three state of the art non-linear regression algorithms. In the study, we also compared the performance using a high quality webcam versus a Kinect sensor. We found, that despite the relatively low quality of the Kinect images it achieves similar performance compared to the high quality camera. These results show that the proposed approach could be extended to estimate POR in a completely non-intrusive way.
机译:在这项工作中,我们研究了一种新技术的可行性,该技术可以估算仅需要从消费类摄像机输入视频的POR。该系统可以在不受控制的光线条件下工作,并且不需要任何复杂的硬件设置。为此,我们提出了一种系统,该系统使用从眼睛区域中提取PCA特征然后进行非线性回归的功能。我们评估了三种最新的非线性回归算法。在研究中,我们还比较了使用高质量网络摄像头和Kinect传感器的性能。我们发现,尽管Kinect图像的质量相对较低,但与高质量相机相比,它仍可达到类似的性能。这些结果表明,所提出的方法可以扩展为以一种完全非侵入性的方式估算POR。

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