计算机科学 ›› 2015, Vol. 42 ›› Issue (6): 313-316.doi: 10.11896/j.issn.1002-137X.2015.06.066

• 图形图像与模式识别 • 上一篇    下一篇

基于N-LBP纹理与色度信息的Camshift跟踪算法

徐一鸣,陆 观,顾菊平   

  1. 南通大学电气工程学院 南通226019,南通大学机械工程学院 南通226019,南通大学电气工程学院 南通226019
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金项目(51307089,61273024,61305031),交通运输部应用基础研究项目(2014319813180),江苏省教育厅面上项目(14KJB510030),南通市科技应用研究计划(BK2013019),南通大学自然科学研究专项项目(13ZJ003),江苏省博士后科研资助

Camshift Tracking Algorithm Based on N-LBP Texture and Hue Information

XU Yi-ming, LU Guan and GU Ju-ping   

  • Online:2018-11-14 Published:2018-11-14

摘要: 基于颜色特征的运动目标跟踪算法容易受到光照非均匀变化或阴影的影响,如何利用多种特征联合构造目标模型以提升跟踪性能是一个关键问题。提出了一种新的特征融合运动目标跟踪算法,该算法基于局部二值模式(Local Binary Pattern,LBP)纹理特征,引入光照自适应的局部标准差构造二值模式门槛值,采用统一模式下的N-LBP纹理描述子构造特征直方图,并结合色度信息建立联合直方图,在Camshift算法框架内进行目标跟踪。实验证明,与传统Camshift算法相比,该算法在保证跟踪算法实时性能的同时,可以更好地克服阴影遮挡等导致的非均匀光照变化带来的影响,具有良好的跟踪效果。

关键词: Camshift跟踪,局部二值模式,特征融合,联合特征直方图

Abstract: Color feature tracking algorithms are easily affected by non-homogenous illumination and shadow.How to construct target model with multiple features is a key question for improving tracking performance.A novel feature fusion target tracking algorithm was proposed in this paper.Illumination self-adaptive local standard deviation is introduced to the threshold for local binary pattern,the joint histogram is constructed by improved N-LBP texture descriptor in unified pattern and hue information,and the moving target tracking is conducted within Camshift algorithm framework.The tracking experiments with shadow interference show that the proposed algorithm can overcome the changes of illumination and has more robustness and stability with good real time performance compared with traditional Camshift algorithm.

Key words: Camshift(continuously adaptive mean shift) tracking,Local binary pattern,Feature fusion,Combined feature histogram

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