孔素然. 基于粒子滤波图像帧的视觉跟踪算法研究[J]. 微电子学与计算机, 2012, 29(11): 177-179,184.
引用本文: 孔素然. 基于粒子滤波图像帧的视觉跟踪算法研究[J]. 微电子学与计算机, 2012, 29(11): 177-179,184.
KONG Su-ran. Particle Filter Based Visual Tracking Algorithm of Image Frames[J]. Microelectronics & Computer, 2012, 29(11): 177-179,184.
Citation: KONG Su-ran. Particle Filter Based Visual Tracking Algorithm of Image Frames[J]. Microelectronics & Computer, 2012, 29(11): 177-179,184.

基于粒子滤波图像帧的视觉跟踪算法研究

Particle Filter Based Visual Tracking Algorithm of Image Frames

  • 摘要: 研究目标物体的图像准确跟踪定位问题.本文主要针对传统的目标跟踪算法中由于视频图像的复杂性,同时运动突变性的存在,使得运动间的关联性被大幅降低,跟踪结果出现较大偏差,难以准确跟踪视频图像,提出了一种粒子滤波优化图像帧视觉跟踪新技术.算法引入了随机分布的运动突变影响算子,在运动估计过程中作为惩罚因子出现,同时采用粒子滤波视觉目标采样视频图像,从而得到实时的跟踪.实验结果表明,提出的方法避免了传统跟踪算法的延时,能够精确实时定位目标物体.

     

    Abstract: Research the object image accurately tracking problem.This article mainly aims at the traditional target tracking algorithm for video image complexity, while movement mutation existence, making movement between relevance is substantially reduced, tracking results appear larger deviation, it is difficult to accurately track the video image, proposes a kind of particle filter optimization of image frames for visual tracking of new technologies.The algorithm introduced random motion mutations affecting the operator, in the motion estimation process as the penalty factor, at the same time using particle filter visual target sample video image, so as to obtain the real time tracking.The experimental results show that the method proposed in this paper, to avoid the traditional tracking algorithm for delay, can accurate real-time positioning objects.

     

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