›› 2012, Vol. 42 ›› Issue (05): 1273-1279.

Previous Articles     Next Articles

Temporal-frequency denoising application in event detection base on image sequences

WU Jian-rong1, LI Jun-ying1, LIU Hai-tao1,2   

  1. 1. Key Lab of Wireless Sensor Network and Communications, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Science, Shanghai 200050, China;
    2. Wuxi SensingNet Industrialization Research Institute, Wuxi 214135, China
  • Received:2011-07-04 Online:2012-09-01 Published:2012-09-01

PDF (PC)

781

Abstract: To solve the "false event" detection problem in image sequence analysis in the wild situation with strong background noises, an event detection method based on temporal-frequency denoising is proposed utilizing Kalman filter theory and 2D Discrete Cosine Transform (DCT) theory. The method utilizes Kalman filter to denoise the background model of image sequence with several frames in time domain. The background model is reconstructed adaptively based on variational foreground region. Then, the foreground image of a single frame is denoised utilizing 2D DCT transform. Finally, the event foreground is segmented by adaptive segmentation method. Based on the results of simulation analysis of image sequences collected in wild situation, the proposed method is proved to detect the event foreground and solve the "false event" detection problem effectively and practically, while its F-measure can achieve 0.9423.

Key words: computer application, event detection, kalman filter, 2D DCT

CLC Number: 

  • TP277
[1] Maybank S,Tan T. Introduction-special section on visual surveillance[J]. International Journal of Computer Vision,2000,37 (2):173.
[2] Haritaoglu I, Harwood D, Davis L W. Real-time surveillance of people and their activities[J]. IEEE Trans Pattern Analysis and Machine Intelligence, 2000, 22 (8): 809-830.
[3] 宫晓燕, 汤淑明. 基于非参数回归的短时交通流量预测与事件检测综合算法[J]. 中国公路学报, 2003, 16(1): 82-86. Gong Xiao-yan, Tang Shu-ming. Integrated traffic flow forecasting and traffic incident detection algorithm based on non-param etric regression[J]. China Journal of Highway and Transport, 2003, 16(1): 82-86.
[4] 王亮, 胡卫明, 谭铁牛. 人运动的视觉分析综述[J]. 计算机学报, 2002, 25(3): 225-237. Wang Liang, Hu Wei-ming, Tan Tie-niu. A survey of visual analysis of human motion[J]. Chinese Journal of Computers, 2002, 25(3): 225-237.
[5] 郝志成,朱明,刘微.复杂背景下目标的快速提取与跟踪[J]. 吉林大学学报:工学版,2006,36(2):259-263. Hao Zhi-cheng,Zhu Ming, Liu Wei.Fast extracting and tracking of target in complex environment[J].Journal of Jilin University(Engineering and Technology Edition),2006,36(2):259-263.
[6] 李志慧,张长海,曲昭伟,等.交通流视频检测中背景模型与阴影检测算法[J].吉林大学学报:工学版,2006,36(6):993-997. Li Zhi-hui,Zhang Chang-hai,Qu Zhao-wei,et al.Background extraction model and shadow detection algorithm in traffic flow video detection[J].Journal of Jilin University(Engineering and Technology Edition),2006,36(6):993-997.
[7] Stauffer C, Grimson W. Adaptive background mixture models for real-time tracking//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 1999(2): 246-252.
[8] Karmann Klaus-Peter, Achim von Brandt. Moving object recognition using an adaptive background memory[J]. Time-varying Image Processing and Moving Object Recognition, 2, V Cappellini (ed.), Elsevier Publishers B V, Amsterdam, The Netherlands, 1990: 297-307.
[9] Kilger M. A shadow handler in a video-based real-time traffic monitoring system//Proceedings of IEEE Workshop on Applications of Computer Vision, 1992: 1060-1066.
[10] Elgammal A, Harwood D, Davis L. Non-parametric model for background subtraction//Proceedings of the 6th European Conference on Computer Vision, 2000: 751-767.
[11] Collins R, Lipton A, Kanade T. Introduction to the special section on video surveillance[J]. IEEE Trans Pattern Analysis and Machine Intelligence, 2000, 22 (8): 745-746.
[12] 任臣, 张覃平. 基于Kalman滤波理论的运动目标检测新方法[J]. 光电工程, 2007, 34(4): 7-11. Ren Chen, Zhang Qin-ping. New method for detecting of moving targets based on kalman filter theory[J]. Opto-Electronic Engineering, 2007, 34(4): 7-11.
[13] 沈宇键, 何昕, 郝志航. 图像序列中检测运动小目标的递归算法[J]. 光电工程, 2000, 27(2): 9-13. Shen Yu-jian, He Xin, Hao Zhi-hang. Small moving target in image sequence[J]. Opto-Electronic Engineering, 2000, 27(2): 9-13.
[14] Ridder C, Munkelt O, Kirchner H. Adaptive background estimation and foreground detection using kalman-filtering//Proceedings of the International Conference on Recent Advances in Mechatronics, 1995:193-199.
[15] 张文强, 路 红, 陈义东等. 动态场景中的自适应背景建模研究[J]. 中国图象图形学报, 2009, 14(12): 2627-2630. Zhang Wen-qiang, Lu Hong, Chen Yi-dong, et al. Study of adaptive background modeling in nonstationary scene[J]. Journal of Image and Graphics, 2009, 14(12): 2627-2630.
[16] 林佳乙, 于哲舟, 张健,等. 基于背景差分法和帧间差分法的视频运动检测[J]. 仪器仪表学报, 2008, 29(4): 112-115. Lin Jia-yi, Yu Zhe-zhou, Zhang Jian, et al. A new moving detection method based on background differencing and coterminous frames differencing[J]. Chinese Journal of Scientific Instrument, 2008, 29(4): 112-115.
[17] Rafael C Gonzalez, Richard E Woods. 数字信号处理[M]. 2版.阮秋琦译. 北京:电子工业出版社, 2003: 445-451.
[18] 金良海, 熊才权, 李德华. 自适应型中心加权的中值滤波器[J]. 华中科技大学学报:自然科学版, 2008, 36(8): 10-12. Jin Liang-hai, Xiong Cai-quan, Li De-hua. Adaptive center-weighted median filter[J]. J Huazhong Univ of Sci & Tech(Natural Science Edition), 2008, 36(8): 10-12.
[19] White B, Shah M. Automatically tuning background subtraction parameters using particle swarm optimization//Proceedings of IEEE International Conference on Multimedia and Expo, 2007: 1826-1829.
[1] LIU Fu,ZONG Yu-xuan,KANG Bing,ZHANG Yi-meng,LIN Cai-xia,ZHAO Hong-wei. Dorsal hand vein recognition system based on optimized texture features [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1844-1850.
[2] WANG Li-min,LIU Yang,SUN Ming-hui,LI Mei-hui. Ensemble of unrestricted K-dependence Bayesian classifiers based on Markov blanket [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1851-1858.
[3] JIN Shun-fu,WANG Bao-shuai,HAO Shan-shan,JIA Xiao-guang,HUO Zhan-qiang. Synchronous sleeping based energy saving strategy of reservation virtual machines in cloud data centers and its performance research [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1859-1866.
[4] ZHAO Dong,SUN Ming-yu,ZHU Jin-long,YU Fan-hua,LIU Guang-jie,CHEN Hui-ling. Improved moth-flame optimization method based on combination of particle swarm optimization and simplex method [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1867-1872.
[5] LIU En-ze,WU Wen-fu. Agricultural surface multiple feature decision fusion disease judgment algorithm based on machine vision [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1873-1878.
[6] LI Ju-peng,ZHANG Zu-cheng,LI Mo-yu,MIAO De-fang. Smooth tracking with a kalman filter algorithm for capacitive touch panels [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1910-1916.
[7] OUYANG Dan-tong, FAN Qi. Clause-level context-aware open information extraction [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1563-1570.
[8] LIU Fu, LAN Xu-teng, HOU Tao, KANG Bing, LIU Yun, LIN Cai-xia. Metagenomic clustering method based on k-mer frequency optimization [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1593-1599.
[9] GUI Chun, HUANG Wang-xing. Network clustering method based on improved label propagation algorithm [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1600-1605.
[10] LIU Yuan-ning, LIU Shuai, ZHU Xiao-dong, CHEN Yi-hao, ZHENG Shao-ge, SHEN Chun-zhuang. LOG operator and adaptive optimization Gabor filtering for iris recognition [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1606-1613.
[11] CHE Xiang-jiu, WANG Li, GUO Xiao-xin. Improved boundary detection based on multi-scale cues fusion [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1621-1628.
[12] ZHAO Hong-wei, LIU Yu-qi, DONG Li-yan, WANG Yu, LIU Pei. Dynamic route optimization algorithm based on hybrid in ITS [J]. 吉林大学学报(工学版), 2018, 48(4): 1214-1223.
[13] HUANG Hui, FENG Xi-an, WEI Yan, XU Chi, CHEN Hui-ling. An intelligent system based on enhanced kernel extreme learning machine for choosing the second major [J]. 吉林大学学报(工学版), 2018, 48(4): 1224-1230.
[14] FU Wen-bo, ZHANG Jie, CHEN Yong-le. Network topology discovery algorithm against routing spoofing attack in Internet of things [J]. 吉林大学学报(工学版), 2018, 48(4): 1231-1236.
[15] CAO Jie, SU Zhe, LI Xiao-xu. Image annotation method based on Corr-LDA model [J]. 吉林大学学报(工学版), 2018, 48(4): 1237-1243.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd