Computer Science ›› 2015, Vol. 42 ›› Issue (Z11): 199-202.

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Research on Moving Objects Detection in Video Sequences Based on Grabcut-guassian Mixture Model

SHENG Jia-chuan and YANG Wei   

  • Online:2018-11-14 Published:2018-11-14

Abstract: To detect moving objects accurately and rapidly from the videos sequences,this paper proposed a novel G-GMM method for automatic detection via combination of GMM and Grabcut techniques in image processing.Firstly,this algorithm uses GMM(Gaussian Mixture Model) based background subtraction to produce binary images for every mo-ving object and then constructs their minimum marking rectangles.And then it follows the image information initialization of each marking rectangle via Grabcut.Finally,an iterative algorithm with foreground parameters is adopted to optimize the object segmentation and thus the moving object contour is obtained.Experimental results indicate that the proposed method achieves good accuracy and robustness in the still camera outdoor video surveillance system,providing promising detection results for both rigid and non-rigid objects.

Key words: Object detection,Grabcut-gaussian mixture model(G-GMM),Foreground motion,Image segmentation

[1] Khare M,Srivastava R K,Khare A.Moving object segmentation in Daubechies complex wavelet domain[J].Signal Image and Video Processing,2015,9(3):635-650
[2] 文嘉俊,徐勇,战荫伟.基于AdaBoost和帧间特征的人数统计[J].中国图象图形学报,2014,16(9):1729-1735
[3] 刘赏,董林芳.人群运动方向异常检测算法[J].计算机科学,2013,40(11A):337-340
[4] Trulls E,Tsogkas S,Kokkinos I,et al.Segmentation-aware deformable part models[C]∥IEEE International Conference on Computer Vision and Pattern Recognition(CVPR).2014:168-175
[5] 张欢,安国成,张凤军,等.多颜色空间融合的人体检测算法研究[J].中国图象图形学报,2011,16(10):1944-1950
[6] Ramirez-Quintana J A,Chacon-Murguia M I.Self-adaptiveSUM-CNN neural system for dynamic object detection in normal and complex scenarios[J].Pattern Recognition,2015,48(4):1137-1149
[7] Stauffer C,Grimson W E L.Adaptive background mixture mo-dels for real time tracking[C]∥IEEE International Conference on Computer Vision and Pattern Recognition(CVPR).1999:246-252
[8] Stauffer C,Grimson W E L.Learning patterns of activity using real-time tracking[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2000,22(8):747-757
[9] 程全,马军勇.基于改进高斯混合模型的运动目标检测方法[J].计算机科学,2014,41(7):318-321
[10] Zhao Qin-pei,Ville H,Ismo K.Random swap EM algorithm for Gaussian Mixture Models[J].Pattern Recognition Letters,2012,33(16):2120-2126
[11] Nazre B,Rama R.Detection and inpainting of facial wrinklesusing texture orientation fields and markov random field mode-ling[J].IEEE Transactions on Image Processing,2014,23(9):3773-3788
[12] 周良芬,何建农.基于GrabCut改进的图像分割算法[J].计算机应用,2013,33(1):49-52
[13] Tao Wen-bing,Li Kun-qian,Sun Kun.SaCoseg:object coseg-mentation by shape conformability[J].IEEE Transactions on Image Processing,2015,24(3):943-955
[14] 周爱民,张青富,张桂戌.一种基于混合高斯模型的多目标进化算法[J].软件学报,2014,25(5):913-928
[15] Zhu H,Ding M,Li Y.Gibbs phenomenon for fractional Fourier series[J].IET Signal Processing,2011,5(8):728-738
[16] Chen Ning,Ding Fei.Flame object segmentation by an improved frame difference method[C]∥Third International Conference on Digital Manufacturing and Automation(ICDMA).2012:422-425
[17] Barnich O,Droogenbroeck M V.Vibe:a powerful random technique to estimate the background in video sequences[C]∥IEEE International Conference on Acoustics,Speech and Signal Processing(ICASSP).2009:945-948
[18] Mofaddel M A,Abd-Elhafiez W M.Fast and accurate approa-ches for image and moving object segmentation[C]∥International Conference on Computer Engineering & Systems(ICCES).2011:252-259

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