全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于块计数的交通背景实时更新方法

, PP. 79-84

Keywords: 交通工程,背景更新,背景建模,实时性,高斯模型

Full-Text   Cite this paper   Add to My Lib

Abstract:

为了提高运动目标检测质量,提出以了一种新的基于块计数的选择性背景更新方法,在线学习像素块的变化。首先对传统的中值滤波方法进行改进,基于此方法建立视频的初始背景;然后对训练序列中相邻帧的对应块做临时差,对差值在阀值范围内的块进行累加计算并将结果保存在计数器中,通过对计数器的实时监测,有选择性的根据当前帧和背景中的块值对背景进行更新。结果表明与标准的码本方法相比,提出的方法在视频2的学习速度、前景提取速度、准确率方面分别提高了10%、3%和5%;与高斯混合模型、码本、统计和知识库方法相比,该方法在学习和检测时间上比其他方法快;在检测结果上,从真报警率和误报警率看有较高的辨别度,检测错误的像素比较少。

References

[1]  Vacchetti L,Lepetit V,Fua F.Stable real-time 3D tracking using online and offline information[J].Pattern Analysis and Machine Intelligence,2004,26(10):1385-1391.
[2]  Lee P H,Chiu T H,Lin Y L,et al.Real-time pedestrian and vehicle detection in video using 3D cues[C]//IEEE.2009 IEEE International Conference on Multimedia and Exp(ICME).New York:IEEE press,2009:614-617.
[3]  Ghosh N,Bhanu B.Incremental unsupervised three-dimensional vehicle model learning from video[J].Intelligent Transportation Systems, 2010,11(2):423-440.
[4]  Leotta M J,Mundy J L.Vehicle surveillance with a generic,adaptive,3D vehicle model [J].Pattern Analysis and Machine Intelligence,2011,33(7):1457-1469.
[5]  Nicholas A M,Iphigenia K,Chris T K.A background subtraction algorithm for detecting and tracking vehicles[J].Expert Systems with Applications,2011,38(3):1619-1631.
[6]  Movshovitz A Y,Peleg S.Bacteria-Filters:persistent particle filters for background subtraction [C]//IEEE.IEEE International Conference Image Processing(ICIP),Hongkong:IEEE press,2010,26-29 Sept:677-680.
[7]  Bianco A,Giaccone P,Leonardi E,et al.A Framework for differential frame-based matching algorithms in input-queued switches[C]//IEEE.Twenty-third AnnualJoint Conference of the IEEE Computer and Communications Societies(INFOCOM),Italy:IEEE Press,2004:1147-1157.
[8]  Wayne Power P,Johann A.Schoonees.Understanding background mixture models for foreground segmentation[C]//IEEE.Proceedings of Image and Vision Computing.Auckland:IEEE press,2002:267-271.
[9]  Zivkovic Z.Improved adaptive gaussian mixture model for background subtraction[C]//IEEE.Proceedings of the 17th International Conference on Pattern Recognition.Cambridge:IEEE press,2004,23-26.
[10]  Ismail H,David H,Larry S.Real-time surveillance of people and their activities[J].Pattern Analysis and Machine Intelligence,2000,22(8):809-830.
[11]  张 丽,李志能.自适应背景更新模型基于在HSV空间阴影检测车辆检测[J].中国图象图形学报,2003,8(7):778-782. ZHANG li,LI Zhi-neng.Adaptive background update model based on shadow detection in HSV space for vehicle detection[J].Journal of Image and Graphics,2008,8(7):778-782.(in Chinese)
[12]  Cucchiara R,Grana C,Piccardi M,et al.Statistic and knowledge-based moving object detection in traffic scene[C]//IEEE.Proceedings of the 3th IEEE Conference on Intelligent Transportation Systems.Dearborn:USA IEEE Computer Society Press,2000:27-32.
[13]  Kim K,Chalidabhonse T H,Harwood D,et al.Real-time foreground-background segmentation using codebook model[J].Real-Time Imaging,2005,11(3):167-256.
[14]  Haritaogu I,Harwood D,Davis L.Real-time surveillance of people and their activities[J].IEEE Transaction on Pattern Analysis and Machine Intelligence,2000,22(8):809-830.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133