Real-time algorithm for the detection and classification of the exceptions in the home security surveillance
-
摘要: 同时具有好的实时性和稳健性是基于视频的安全监控系统异常检测算法的难点问题.在家庭安全监控系统中同时利用像素的亮度分量和色度分量检测变化像素,解决摄像镜头由于大尺寸对象闯入引起的图像背景变化造成运动对象检测失败的问题;提出一种实时运动对象分类算法,综合利用开关灯检测、运动距离分析和皮肤探测多种方法,区分是否出现影响家庭安全的事件;提出3关键值背景维护算法,用于消除背景振动像素,减少虚假报警.实验表明,本文异常探测算法对视频监控系统异常探测和消除虚假异常报警具有较好的实时性和稳健性.Abstract: Fast and robust detection of moving objects was difficult for a security surveillance system based PC. By combing the illumination and the chroma in the YUV color space, the problem was solved that a big breaking-in object causes the background pixels to change its illumination. A fast method for analyzing and classifying the moving objects was introduced, based on some detection such as light switching, moving distance and skins. In order to eliminate swaying objects in the background and to reject false alarms, a new method of background maintenance was proposed.
-
Key words:
- surveillance /
- moving pixel detection /
- background maintenance /
- morphological operation
-
[1] Iketani A, Kuno Y, Shimada N, et al. Real time surveillance system detecting persons in complex scenes. Proceedings of Image Analysis and Processing, 1999. 1112~1115 [2] Barron J, Fleet D, Beauchemin S. Performance of optical flow techniques [J]. International Journal of Computer Vision, 1994, 12(1):42~77 [3] Anderson C, Burt P, van der Waals G. Change detection and tracking using pyramid transformation techniques. Proc of SPIE-intelligent Robots and Computer Vision, 1985. 579:72~78 [4] Collins R T. A system for video surveillance and monitoring. CMU-RI-TR-00-12. http://www.cs. cmu.edu [5] Wildes R P. A measure of motion salience for surveillance applications. Proceedings of Image Processing ICIP 98, 1998.183~187 [6] 章毓晋. 图像处理和分析[M]. 北京:清华大学出版社, 1999. 29~30 Zhang Yujin. Image processing and analysis [M]. Beijing:Tsinghua University Press, 1999. 29~30(in Chinese) [7] Wu H Y, Chen Q. Face detection from color images using a fuzzy pattern matching method [J]. IEEE Transaction On Pattern Analysis and Machine Intelligence, 1999,21(6):557~563 [8] Sangwine S J, Horne R E N. The colour image processing handbook[M]. Chapman & Hall, 1998. 82~89 [9] Toyama K, Krumm J, Brumitt B, et al. Wallflower:Principles and practice of background maintenance. Proc of Computer Vision, 1999. 255~261 [10] Wren C, Azarbayejani A, Darrell T, et al. Pfinder:real-time tracking of the human body [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(7):780~785 [11] Grimson W E L, Stauffer C. Adaptive background mixture models for real-time tracking. CVPR, 1999. 23~25
点击查看大图
计量
- 文章访问数: 2729
- HTML全文浏览量: 122
- PDF下载量: 4
- 被引次数: 0