红外技术2016，Vol.38Issue(5)：389-395,7.
基于协方差描述子稀疏表示的前视红外建筑物目标跟踪锁定
Forward-looking-infrared Building Object Tracking Based on Sparse Representation of Covariance Descriptor
杨春伟 1王仕成 2廖守亿 1刘华平1
作者信息
- 1. 第二炮兵工程大学精确制导仿真技术实验室，陕西西安 710025
- 2. 清华大学计算机科学与技术系，北京 100084
- 折叠
摘要
Abstract
As the key component of forward-looking-infrared(FLIR) image terminal guidance, infrared object tracking is a challenging task. In this paper, a FLIR building object tracking framework based on sparse representation of covariance descriptor(Cov) is proposed. First, the Cov of FLIR building is extracted and then transformed to Euclidean space due to the reason that Cov lies in Riemannian space. Then, based on particle filter theory, the observation model of object is represented through sparse representation of template dictionary, and object tracking is continued by using a Bayesian state inference framework. Experiments on FLIR building object show that the proposed method obtains effectiveness in tracking accuracy and robustness.关键词
红外建筑物/目标跟踪锁定/稀疏表示/协方差描述子/仿射变换Key words
infrared building/object tracking/sparse representation/covariance descriptor/affine transformation分类
信息技术与安全科学引用本文复制引用
杨春伟,王仕成,廖守亿,刘华平..基于协方差描述子稀疏表示的前视红外建筑物目标跟踪锁定[J].红外技术,2016,38(5):389-395,7.
