计算机工程

• 图形图像处理 • 上一篇    下一篇

基于卡尔曼滤波自上向下的动态阴影检测与跟踪

张正本1,蔡鹏飞1,孙挺2   

  1. (1.河南工学院 计算机科学与技术系,河南 新乡 453000;2.西北大学 可视化研究所,西安 710069)
  • 收稿日期:2016-01-25 出版日期:2017-02-15 发布日期:2017-02-15
  • 作者简介:张正本(1979—),男,实验师、硕士,主研方向为图形图像处理;蔡鹏飞,实验师、硕士;孙挺,副教授、博士研究生。
  • 基金项目:
    河南省教育厅科学技术研究重点项目(13A520221,14A520045);河南省教育科学“十二五”规划课题([2012]-JKGHAC-0116*)。

Top-down Dynamic Shadow Detection and Tracking Based on Kalman Filtering

ZHANG Zhengben 1,CAI Pengfei 1,SUN Ting 2   

  1. (1.Department of Computer Science and Technology,Henan Institute of Technology,Xinxiang,Henan 453000,China; 2.Institute of Visualization,Northwestern University,Xi’an 710069,China)
  • Received:2016-01-25 Online:2017-02-15 Published:2017-02-15

摘要: 目前多数阴影检测方法局限于半影阴影,不能很好地应对本影阴影。针对该问题,引入卡尔曼滤波,提出一种自上向下的动态阴影检测与跟踪方法。利用梯度信息获得目标的轮廓信息以改进前景分割过程,分析每个潜在阴影的纹理相似性和亮度失真的空间相似性,在数据关联框架中结合卡尔曼滤波,利用目标和阴影之间的时间一致性提高阴影检测率。在多个数据集上的实验结果表明,该方法稳定高效,与几何信息法、颜色空间差异法和多级方法相比,其平均阴影辨别率较高。

关键词: 阴影检测与跟踪, 卡尔曼滤波, 时间一致性, 前景分割, 梯度, 阴影检测

Abstract: As most shadow detection methods are limited by penumbral shadows and cannot process umbra shadow well,a top-down dynamic shadow detection and tracking method based on Kalman Filtering(KF) is proposed.Firstly,contour information of the target is obtained by gradient information,and foreground segmentation is also improved.Then,the similarity of texture and spatial similarity of brightness distortion for each potential shadow are analyzed.Finally,in the frame of data association,time consistency between target and shadow is used to increase shadow detection rate,combining with KF.Experimental results on several data sets show that the proposed method is stable and efficient.Compared with geometry information method,color space difference method and multi-level method,it has higher average shadow identification rate.

Key words: shadow detection and tracking, Kalman Filtering(KF), time consistency, foreground segmentation, gradient, shadow detection

中图分类号: