An Object Extraction Method of Multi-model Cooperation

doi:10.3969/j.issn.1000-3428.2015.05.047

Abstract

Abstract: Gaussian Mixture Model(GMM) is adopted to solve foreground detection problems. However,GMM can not detect objects in which do not move in the scene. This paper proposes the multi-model cooperative method to detect foreground objects in complex scene. Under the assumption that the camera is fixed,it first uses the adaptive GMM to build a background which is updated by the light detection model and the scene detection model. A shadow detection model is also used in this paper at last. It mades a comparison with two algorithms. Experimental results show that this method can completely extract the object contour,and single frame processing time is less.

Key words: object extraction, Gaussian Mixture Model(GMM), light detection model, scene state detection model, shadow detection model, background update

摘要： 固定摄像机目标提取多以高斯混合模型为背景模型,在检测运动缓慢、间歇停滞的目标时会出现前景目标空洞的问题。为此,提出一种能够适应目标间歇停滞的多模型协同目标提取方法。采用高斯混合模型进行背景学习,通过光线检测模型和场景状态检测模型协同控制背景适时更新,利用阴影检测模型剔除阴影。实验结果表明, 与KaewTraKulPong P 方法相比,该方法能较完整地提取到目标轮廓,且单帧处理时间较少。

关键词: 目标提取, 高斯混合模型, 光线检测模型, 场景状态检测模型, 阴影检测模型, 背景更新

CLC Number:

TP391.41

JI Xuye,CHEN Ming,FENG Guofu,ZHAO Haile. An Object Extraction Method of Multi-model Cooperation[J]. Computer Engineering.

冀续烨,陈明,冯国富,赵海乐. 一种多模型协同的目标提取方法[J]. 计算机工程.

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URL:

https://www.ecice06.com/EN/Y2015/V41/I5/254

References

(上接第258 页) 参考文献 [ 1 ]　许新征,丁世飞,史忠植,等. 图像分割的新理论和新方法[J]. 电子学报,2010,38(2):76-82. [ 2 ]　Li Wei,Wu Xiaojuan,Matsumoto K,et al. Foreground Detection Based on Optical Flow and Background Subtract [ C ] / / Proceedings of IEEE International Conference on Communications,Circuits and Systems. Washington D. C. ,USA:IEEE Press,2010:359-362. [ 3 ]　Gupta K,Kulkarni A V. Implementation of an Automated Single Camera Object Tracking System Using Frame Differencing and Dynamic Template Matching[EB/ OL]. [ 2014-02-21 ]. http:/ / link. springer. com/ chapter / 10. 1007% 2F978-1-4020-8741-7_44#. [ 4 ]　Zhou Wei, Liu Yu, Zhang Weiming, et al. Dynamic Background Subtraction Using Spatial-color Binary Patterns [ C ] / / Proceedings of the 6th International Conference on Image and Graphics. Washington D. C. , USA:IEEE Press,2011:314-319. [ 5 ]　Hsiao P Y. A Region-based Background Modeling and Subtraction Using Partial Directed Hausdorff Distance[ C] / / Proceedings of ICRA’04. Washington D. C. , USA:IEEE Press,2004:956-960. [ 6 ]　Fiala M,Shu Chang. Background Subtraction Using Selfidentifying Patterns [ C ] / / Proceedings of the 2nd Canadian Conference on Computer and Robot Vision. Washington D. C. ,USA:IEEE Press,2005:558-565. [ 7 ]　穆亚东,周秉锋. 基于颜色和纹理信息的快速前景提取方法[J]. 计算机学报,2009,32(11):2252-2257. [ 8 ]　Wan Qin, Wang Yaonan. Multiple Moving Objects Tracking under Complex Scenes [C] / / Proceedings of the 6th World Congress on Intelligent Control and Automation. Washington D. C. ,USA:IEEE Press,2006: 9871-9875. [ 9 ]　Stauffer C, Grimson W E L. Adaptive Background Mixture Models for Real-time Tracking [ C ] / / Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Washington D. C. , USA:IEEE Press,1999:252-255. [10]　Stenger B,Ramesh V,Paragios N,et al. Topology Free Hidden Markov Models: Application to Background Modeling[C]/ / Proceedings of the 8th IEEE International Conference on Computer Vision. Washington D. C. ,USA: IEEE Press,2001:294-301. [11]　李百惠,杨　庚. 高斯混合模型的自适应前景提取[J]. 中国图象图形学报,2013,18(12):1620-1627. [12]　Kaewtrakulpong P, Bowden R. An Improved Adaptive Background Mixture Model for Real-time Tracking with Shadow Detection [ M ] / / Remagnino P, Graeme A, Paragios J N,et al. Video-based Surveillance Systems. Berlin,Germany:Springer,2002:135-144. 编辑　刘　冰

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