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Real-time gaze estimation using a Kinect and a HD webcam

机译:使用Kinect和高清网络摄像头进行实时注视估计

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摘要

In human-computer interaction, gaze orientation is an important and promising source of information to demonstrate the attention and focus of users. Gaze detection can also be an extremely useful metric for analysing human mood and affect. Furthermore, gaze can be used as an input method for human-computer interaction. However, currently real-time and accurate gaze estimation is still an open problem. In this paper, we propose a simple and novel estimation model of the real-time gaze direction of a user on a computer screen. This method utilises cheap capturing devices, a HD webcam and a Microsoft Kinect. We consider that the gaze motion from a user facing forwards is composed of the local gaze motion shifted by eye motion and the global gaze motion driven by face motion. We validate our proposed model of gaze estimation and provide experimental evaluation of the reliability and the precision of the method.
机译:在人机交互中,注视定向是显示用户注意力和焦点的重要且有希望的信息来源。注视检测对于分析人的情绪和情感也可能是非常有用的指标。此外,凝视可以用作人机交互的输入方法。然而,当前的实时和准确的注视估计仍然是未解决的问题。在本文中,我们提出了一种简单新颖的用户在计算机屏幕上实时注视方向的估计模型。这种方法利用廉价的捕获设备,高清网络摄像头和Microsoft Kinect。我们认为,来自面向前方的用户的凝视动作由眼动引起的局部凝视动作和由脸部动作驱动的整体凝视动作组成。我们验证了我们提出的凝视估计模型,并提供了对该方法的可靠性和准确性的实验评估。

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