To reduce the influence of complex environment like illumination variation, appearance change and partial occlusion during the object tracking in the sequence images, a hybrid particle filter tracking method based on global and local information is proposed. The local binary patterns (LBP) textual feature is introduced into the particle filter algorithm. Through sparse coding target sub-block, the local information is fully used, and the global information is taken into account to determine the position of target in the current frame. During the tracking, the robustness of the tracking algorithm is improved since the template is updated in real time. Experimental results show that the proposed tracking algorithm achieves good results in complex background.
作者简介: 周治平,男,1962年生,博士,教授,主要研究方向为检测技术与自动装置.Email:zzping@jiangnan.edu.cn.(ZHOU Zhiping, born in 1962, Ph.D., professor. His research interests include detection technology and automatic equipment.)周明珠(通讯作者),女,1988年生,硕士,主要研究方向为图像处理、目标跟踪.Email:6121905018@vip.jiangnan.edu.cn.(ZHOU Mingzhu(Corresponding author), born in 1988, master. Her research interests include image processing and object tracking.)李文慧,女,1989年生,硕士,主要研究方向为图像处理、目标识别.Email:6121904004@vip.jiangnan.edu.cn.(LI Wenhui, born in 1989, master. Her research interests include image processing and object recognition.)
引用本文:
周治平,周明珠,李文慧. 基于混合粒子滤波和稀疏表示的目标跟踪算法[J]. 模式识别与人工智能, 2016, 29(1): 22-30.
ZHOU Zhiping, ZHOU Mingzhu, LI Wenhui. Object Tracking Algorithm Based on Hybrid Particle Filter and Sparse Representation. , 2016, 29(1): 22-30.