电子学报 ›› 2018, Vol. 46 ›› Issue (2): 479-485.DOI: 10.3969/j.issn.0372-2112.2018.02.030

• 学术论文 • 上一篇    下一篇

基于光流与Delaunay三角网格的图像序列运动遮挡检测

张聪炫1,2, 陈震1,2, 汪明润1, 黎明1, 江少锋2   

  1. 1. 南昌航空大学江西省图像处理与模式识别重点实验室, 江西南昌 330063;
    2. 南昌航空大学测试与光电工程学院, 江西南昌 330063
  • 收稿日期:2016-10-13 修回日期:2016-12-15 出版日期:2018-02-25 发布日期:2018-02-25
  • 通讯作者: 陈震
  • 作者简介:张聪炫,男,1984年7月生,河南焦作人.分别于2007年、2014年在南昌航空大学和南京航空航天大学获得学士、博士学位.现为南昌航空大学讲师,硕士生导师,主要研究方向为图像检测与智能识别.E-mail:zcxdsg@163.com
  • 基金资助:
    国家自然科学基金(No.61401190,No.61462062);航空科学基金(No.2015ZC56009);江西省重点研发计划项目(No.20161BBE50080);江西省图像处理与模式识别重点实验室开放基金(No.TX201604001);无损检测技术教育部重点实验室开放基金(No.ZD201529001)

Motion Occlusion Detecting from Image Sequence Based on Optical Flow and Delaunay Triangulation

ZHANG Cong-xuan1,2, CHEN Zhen1,2, WANG Ming-run1, LI Ming1, JIANG Shao-feng2   

  1. 1. Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition, Nanchang Hangkong University, Nanchang, Jiangxi 330063, China;
    2. School of Measuring and Optical Engineering, Nanchang Hangkong University, Nanchang, Jiangxi 330063, China
  • Received:2016-10-13 Revised:2016-12-15 Online:2018-02-25 Published:2018-02-25

摘要: 针对图像序列运动遮挡检测的准确性与鲁棒性问题,提出一种基于光流与Delaunay三角网格的图像序列运动遮挡检测方法.首先构造基于非局部约束的TV-L1光流估计模型;然后根据图像Delaunay三角网格划分与光流估计结果对图像序列帧间对应像素点和局部三角形进行运动遮挡判断并检测遮挡区域;最后采用MPI Sintel和Middlebury数据库提供的测试图像集对本文方法与SMOD、GOSF等代表性方法进行对比测试.实验结果表明,本文方法相对于SMOD和GOSF方法在十组测试图像集的平均漏检率和误检率分别降低15.21%与30.57%,说明本文方法针对非刚性运动、复杂场景、弱纹理、光照阴影以及大位移等类型图像序列均具有较高的检测精度和较好的鲁棒性.

关键词: 图像序列, 遮挡检测, 光流, Delaunay三角网格

Abstract: For the accuracy and robustness of the motion occlusion detecting from image sequence,this paper proposes a novel occlusion detection method based on the optical flow and Delaunay triangulation.Firstly,a TV-L1 optical flow model based on the non-local constraint is presented.Secondly,according to the results of the Delaunay triangulation and optical flow result of image sequence,the occlusion of the corresponding pixels and local triangles between the continuous frames is located and the motion occlusion regions could be detected.Finally,the evaluation sequences of the MPI Sintel and Middlebury databases are employed to test the performance of the motion occlusion detecting between the proposed method,the SMOD and GOSF methods.The experimental results show that the average omission rate and average false rate of the proposed method on the ten test image sequences are reducing 15.21% and 30.57% compared to the SMOD and GOSF methods,which indicates the proposed method has the higher accuracy and better robustness of the motion occlusion detecting under the non-rigid motion,complex scene,weak texture,brightness shadow and large displacement.

Key words: image sequence, occlusion detection, optical flow, Delaunay triangulation

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