一种基于粒子滤波的瞳孔跟踪方法

Wang Changyuan, Jiang Guangyi, Chen Hua, Jin Ruiming
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引用次数: 1

摘要

眼动追踪技术在国内外引起了越来越多的关注,成为众多学科的研究热点。局部瞳孔跟踪是非常重要的。粒子滤波作为处理非线性和非高斯滤波问题的主要手段,克服了卡尔曼滤波的缺点,对过程噪声和观测噪声没有分布限制。而SIR (Sequential Importance Resampling)采样方法可以消除传统粒子滤波中粒子的退化。本文采用基于SIR的粒子滤波方法对瞳孔进行跟踪。实验表明,该方法能够准确、实时地跟踪瞳孔,具有较高的研究和应用价值。
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A pupil tracking method based on particle filter
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.
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