摘要
为实现无人直升机的地标跟踪,将在线特征选择过程嵌入粒子滤波算法,采用自适应的状态转移模型,在跟踪过程中利用R、G、B值的线性组合作为候选特征集,对特征的目标区域和背景区域的颜色直方图分布进行统计,根据获得的对数似然比,选择区分度最好的特征计算似然图像,并通过2种途径获得2组粒子,用于估计目标位置。实验结果表明,该算法跟踪精度较高,鲁棒性较强。
In order to realize landmark tracking by Unmanned Aerial Vehicle（UAV）, this paper embeds online feature selection into particle filtering algorithm, and adopts adaptive transition model. Candidate feature set is composed of linear combination of R, G and B pixel values. Histograms of feature values for pixels on the object and in the background are computed for obtaining log likelihood ratio and variance ratio. The feature with the best discrimination is selected for computing the likelihood image. Two sets of particles are obtained via different approaches for estimating the position of the object. Experimental results show that the algorithm provides more reliable results and it is more robust.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第24期155-157,共3页
Computer Engineering
基金
国家"863"计划基金资助项目(2006AA10Z204)
关键词
粒子滤波
特征选择
无人直升机
目标跟踪
地标
particle filtering
feature selection
Unmanned Aerial Vehicle（UAV）
object tracking
landmark
