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中文摘要：
针对视频目标突变转向时产生的重尾问题，提出了一种变换观测模型的粒子滤波跟踪算法。该算法根据提出的变换准则，目标稳定运动时采用高斯分布观测似然函数，当目标突变转向时采用多变量拉普拉斯分布观测似然函数较好的逼近重尾分布，提高跟踪的精度。视频跟踪仿真试验表明，该算法是稳健的，能够对突变转向的运动目标进行有效、可靠地跟踪。
英文摘要：
To deal with the heavy-tailed issue of the video object with abrupt turns, a particle filter tracking algorithm based on switching observation models is proposed. According to the presented switching rule, to improve the tracking precision, the observation likelihood of Gaussian distribution is used when the object moves steadily, and the observation likelihood of multivariate Laplace distribution is adopted to surmount the heavy-tailed issue when the object turns abruptly. The simulation result shows the algorithm is robust and effective at abrupt mining object tracking.
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