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A Pupil Tracking Method Based on Particle Filter

机译:一种基于粒子滤波器的瞳孔跟踪方法

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Eye tracking technology has attracted more and more attention at home and abroad, becomes a hot topic in many disciplines. The part pupil tracking is very important. As the primary means of dealing with nonlinear and non-Gaussian filtering problem, Particle Filter has overcame the Kalman Filters's defects, it has no distribution limit to process noise and observation noise. While SIR (Sequential Importance Resampling) sampling method can eliminate particle degradation in the traditional particle filter. In this paper, we track the pupil by Particle Filter based on SIR. Experiments show that the method can be accurate and real-time to track the pupil, and it has high value of research and application.
机译:眼跟踪技术在国内外吸引了越来越多的关注,成为许多学科的热门话题。瞳孔跟踪是非常重要的。作为处理非线性和非高斯滤波问题的主要方法,粒子过滤器已经克服了卡尔曼过滤器的缺陷,它没有分配限制来处理噪声和观察噪声。虽然SIR(顺序重要性重采样)采样方法可以消除传统颗粒过滤器中的颗粒劣化。在本文中,我们通过基于SIR的粒子滤波器跟踪瞳孔。实验表明,该方法可以准确且实时跟踪瞳孔,并具有高价值的研究和应用。

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