【作者】 李军； 张华； 单梁；

【Author】 LI Jun,ZHANG Hua,SHAN Liang (School of Automation,NUST,Nanjing 210094,China)

【机构】 南京理工大学自动化学院；

【摘要】 目标自身的形变、复杂背景的干扰以及各类噪声、遮挡、光照等因素都会对目标跟踪产生影响。为了有针对性地提高复杂现实环境下跟踪算法的准确性、鲁棒性与实时性,结合Meanshift算法和粒子滤波器算法的优点,提出了基于Mean shift和粒子滤波器的综合算法。通过度量因子自适应切换Mean shift算法和粒子滤波算法,这样相对于Mean shift算法,增强了算法的鲁棒性,而相对于传统的粒子滤波器算法,增强了其实时性。更多还原

【Abstract】 The disadvantage factors like the deformation of target,the interference of the complex background,various types of noise,shelter and light have a serious influence on the target tracking. In order to improve the accuracy,robustness and real-time performance of the tracking algorithm under the real complex condition,an integrated algorithm is proposed based on Mean shift algorithm and Particle Filter algorithm.The algorithm can switch Mean shift algorithm and Particle Filter algorithm by measurement parameter adaptively,so that we can enhance the stability of the Mean shift algorithm and enhance the real-time nature compared with traditional Particle Filter algorithm.更多还原