基于运动增强和颜色分布比对的运动目标检测

郭江; 谷多玉; 李书晓; 常红星

基于运动增强和颜色分布比对的运动目标检测

中国科学院自动化研究所综合信息系统研究中心, 北京 100190

详细信息

中图分类号: TP 391
计量
- 文章访问数: 3087
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- 被引次数: 0
出版历程
- 收稿日期: 2010-10-22
- 网络出版日期: 2012-02-29

Moving object detection using motion enhancement and color distribution comparison

Integrated Information System Research Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

摘要

摘要: 为检测无人机视频中的地面运动目标,提出了一种运动和颜色信息相结合的算法.采用前向运动历史图像来增强独立运动信息和抑制背景噪声,确保完整分割出候选运动区域; 提出一种迭代的、基于局部颜色分布比对的方法,去除候选区域中的背景像素,以更准确地提取单个运动目标.算法不仅节约了计算量,还有效降低了误检和漏检的可能性.多组无人机视频的实验结果表明了所提算法的高效性和鲁棒性.
- 航空视频分析 /
- 运动目标检测 /
- 前向运动历史图像 /
- 局部颜色分布比对
Abstract: To detect moving objects from videos taken by unmanned aerial vehicles, an approach using motion and color cues was proposed. It adopted the forward motion history image to enhance the independent moving information and suppress the noises in background areas, enabling the candidate moving regions to be extracted entirely. Then, an iterative local color distribution comparison based the method was developed to remove the background pixels contained by each candidate region, insuring each moving object to be extracted precisely. Thus, the cost of computation is saved, and the miss rate and false alarm rate can be cut down prominently. Experimental results with several aerial videos demonstrate the performance and the robustness of the proposed method.
- aerial video analysis /
- moving object detection /
- forward motion history image /
- local color distribution comparison

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参考文献(12)

[1]	Burt P J,Bergen J R,Hingorani R,et al.0bject tracking with a moving camera [C]//Nassau.Proceedings of the IEEE Workshop on Visual Motion.New Jersey:IEEE Computer Society Press,1991:2-12
[2]	Kumar R,Sawhney H,Samarasekera S,et al.Aerial video surveillance and exploitation[J].IEEE Proceddings,2001,89(10):1518-1539
[3]	Ali S,Shah M.Cocoa:tracking in aerial imagery[C]//Daniel J Henry.Airborne Intelligence,Surveillance,Reconnaissance(ISR) Systems and Applications III.Bellingham:SPIE the International Society for Optical Engineering,2006
[4]	Zhao Zhengyin,Collins R.Moving object localization in thermal imagery by forward-backward MHI[C]//Schmid C.IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshop.New York:IEEE Computer Society Press,2006:133-140
[5]	Veit T,Cao F,Bouthemy P.An a contrario decision framework for region-based motion detection[J].International Journal of Computer Vision,2006,68(2):163-178
[6]	Yao F H,Sekmen A,Malkani M.A novel method for real-time multiple moving targets detection from moving IR camera[C]//19th International Conference on Pattern Recognition.Florida:IEEE Computer Society Press,2008:1-4
[7]	Zitova B,Flusser J.Image registration methods: a survey[J].Image and Vision Computing,2003,21(11):977-1000
[8]	Benedek C,Sziranyi T,Kato Z,et al.Detection of object motion regions in aerial Image pairs with a multilayer markovian model[J].IEEE Transactions on Image Processing,2009,18(10):2303-2315
[9]	Canny J.A computational approach to edge detection[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1986,8(6):679-698
[10]	Procerus^TM Technologies.UAV convoy following[EB/OL].http://procerusuav.com/gallery.php
[11]	Collins R,Liu Yanxi,Leordeanu M.Online selection of discriminative tracking features[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2005,27(10):1631-1643
[12]	Kasturi R,Goldgof D,Soundararajan P,et al.Framework for performance evaluation of face,text,and vehicle detection and tracking in video: data,metrics,and protocol[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2009,31(2):319-336