摘要
为了提高背景混淆下的跟踪效果,提出了基于谱直方图和Kalman滤波的目标跟踪方法。通过将图像与滤波器组进行卷积计算获取图像的频率特征,统计获得图像的谱直方图。谱直方图将图像转移到频域进行统计,减少了颜色以及噪声等因素的干扰。为了提高跟踪效率,引入Kalman滤波运动估计,进行局部搜索运动目标,并详细探讨了Kalman参数的设置。实验结果表明,在背景混淆的场景下,相对于颜色直方图来说,该算法能够取得较好的跟踪效果。
To improve the tracking performance with scene complicated backgrounds, a algorithm of object tracking based on spectral histogram and Kalman filter is proposed.To obtain the image＇s frequency characteristic, firstly convoluted with image, and then computed its spectral histogram.Spectral histogram is computed on the frequency domain, so the color and noise interference is reduced.To save the cost of time, Kalman filter is adopted to predict object＇s location, in order to search object on local area.Finally, the parametric setting of Kalman is discussed.The results indicated this algorithm do better than color histogram on the scene with complicated backgrounds.
出处
《计算机工程与设计》
CSCD
北大核心
2010年第6期1387-1389,1393,共4页
Computer Engineering and Design
基金
辽宁省教育厅高等学校攻关计划科研基金项目(202123195)
关键词
谱直方图
KALMAN滤波
目标跟踪
特征提取
智能监控
spectral histogram
Kalman filter
object tracking
feature extraction
intelligent surveillance
