[1]张爱升,张艳彬.基于双目立体视觉的取走物检测技术研究[J].计算机技术与发展,2018,28(06):184-187.[doi:10.3969/ j. issn.1673-629X.2018.06.041]
 ZHANG Ai-sheng,ZHANG Yan-bin.Research on Removed Object Detection Technique Based on Binocular Stereo Vision[J].,2018,28(06):184-187.[doi:10.3969/ j. issn.1673-629X.2018.06.041]
点击复制

基于双目立体视觉的取走物检测技术研究()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年06期
页码:
184-187
栏目:
应用开发研究
出版日期:
2018-06-10

文章信息/Info

Title:
Research on Removed Object Detection Technique Based on Binocular Stereo Vision
文章编号:
1673-629X(2018)06-0184-04
作者:
张爱升张艳彬
南京邮电大学 通信与信息工程学院,江苏 南京 210003
Author(s):
ZHANG Ai-shengZHANG Yan-bin
 School of Telecommunications &Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210003,China
关键词:
取走物检测双目立体视觉运动前景彩色图像深度图像
Keywords:
removed object detectionbinocular stereo visionmotion foregroundcolor imagedepth image
分类号:
TP391
DOI:
10.3969/ j. issn.1673-629X.2018.06.041
文献标志码:
A
摘要:
双目立体视觉技术应用在视频监控领域能使其更加智能化。 对此,提出了一种借助双目立体视觉技术进行取走物检测的方法。 一方面,在深度图像中获取深度变化信息,对深度变化情况进行标记,分为三种区域:深度明显增加的区域、深度明显减少的区域和深度基本不变的区域。 另一方面,在彩色图像中利用改进的 surendra 算法提取运动前景,即对深度增加或基本不变的区域进行背景更新,再利用背景减除法得到运动前景,在前景区域中,符合深度增加或深度基本不变的前景区域即为取走物区域。 最后在光线合适的室内环境中,用提出的取走物检测方法进行了实验,结果表明,该方法能有效地检测出取走物且能显露出被取走物品的大体形状,场景适应性良好。
Abstract:
Binocular stereo vision technology is used in video surveillance and can make it more intellectualized. For this,we propose a object removal detection method based on binocular stereo vision. For one thing,the depth variation information is obtained in the depth image and marked into three areas including the areas with significantly increased depth,the areas with significantly reduced depth and that with little depth variance. For another,the motion foreground is extracted by improved surendra algorithm in the color image,that is,to update the background in the area of depth increase or the little variance,and then using the background subtraction method to obtain the foreground of the motion. At last,the foreground region with depth increase or depth little variance is the removed object region. The experiment is carried out with the method of removed object detection in the indoor environment with appropriate light,which shows that it can effectively detect the removal with general shape and the scene adaptability is better.

相似文献/References:

[1]何海 汤春林 孙华燕.双目立体视觉在模型姿态监测中的应用研究[J].计算机技术与发展,2006,(11):238.
 HE Hai,TANG Chun-lin,SUN Hua-yan.Application of Binocular Stereo Vision in Model Carriage Measure[J].,2006,(06):238.
[2]王瑞 杨润泽 尹晓春.一种改进的立体像对密集点匹配算法[J].计算机技术与发展,2011,(09):70.
 WANG Rui,YANG Run-ze,YIN Xiao-chun.A Modified Image Dense Stereo Matching Algorithm[J].,2011,(06):70.
[3]陆振杰,宋进.单幅数字图像多尺度空间下的场景深度估计[J].计算机技术与发展,2013,(01):51.
 LU Zhen-jie,SONG Jin.Scene Depth Estimation for Single Digital Image in Multi-scaled Space[J].,2013,(06):51.

更新日期/Last Update: 2018-08-22