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Estimating Point of Regard with a Consumer Camera at a Distance

机译:估算远处消费者相机的点

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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,我们研究了一种新颖技术的可行性来估计仅需要从消费者摄像机的视频源的POR。系统可以在不受控制的光线条件下工作,不需要任何复杂的硬件设置。为此,我们提出了一种系统,该系统使用来自眼睛区域的PCA特征提取,然后是非线性回归。我们评估了三个艺术非线性回归算法的状态。在该研究中,我们还将使用高质量的网络摄像头与Kinect传感器进行了比较。我们发现,尽管采用了相对较低的Kinect图像质量,但它与高质量相机相比实现了类似的性能。这些结果表明,可以将所提出的方法以完全非侵入的方式延长以估算POR。

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