Tracking Iris Contour with a 3D Eye-Model for Gaze Estimation
Tracking Iris Contour with a 3D Eye-Model for Gaze Estimation
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DOI：
10.1007/978-3-540-76386-4_65
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发表时间：
2007-11
期刊：
影响因子：
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通讯作者：
Haiyuan Wu;Yosuke Kitagawa;T. Wada;Takekazu Kato;Qian Chen
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文献类型：
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作者：
Haiyuan Wu;Yosuke Kitagawa;T. Wada;Takekazu Kato;Qian Chen
本文介绍了一种利用单目相机跟踪虹膜轮廓和估计眨眼眼睛注视的复杂方法。设计了一个由眼球、虹膜轮廓和眼睑组成的3D眼睛模型，该模型描述了眼睛的几何特性和运动。利用该模型和粒子过滤器对虹膜轮廓和眼睑轮廓进行跟踪。该算法能够检测“纯”虹膜轮廓，因为它可以区分虹膜轮廓和眼睑轮廓。眼睛注视用三维眼睛模型的运动参数来描述，这些运动参数在跟踪过程中由粒子滤波估计出来。该算法的其他显著特点是：1)它不需要任何特殊的光源（例如红外照明器），2)它可以在视频速率下运行。通过对真实视频序列的大量实验，验证了该方法的鲁棒性和有效性。
This paper describes a sophisticated method to track iris contour and to estimate eye gaze for blinking eyes with a monocular camera. A 3D eye-model that consists of eyeballs, iris contours and eyelids is designed that describes the geometrical properties and the movements of eyes. Both the iris contours and the eyelid contours are tracked by using this eye-model and a particle filter. This algorithm is able to detect “pure” iris contours because it can distinguish iris contours from eyelids contours. The eye gaze is described by the movement parameters of the 3D eye model, which are estimated by the particle filter during tracking. Other distinctive features of this algorithm are: 1) it does not require any special light sources (e.g. an infrared illuminator) and 2) it can operate at video rate. Through extensive experiments on real video sequences we confirmed the robustness and the effectiveness of our method.