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基于多幀邊緣差異的視頻運動對象的分割與跟蹤算法

劉龍,  劉貴忠,  王占輝,  王黎明

劉龍, 劉貴忠, 王占輝, 王黎明. 基于多幀邊緣差異的視頻運動對象的分割與跟蹤算法[J]. 電子與信息學報, 2004, 26(5): 715-721.
引用本文: 劉龍, 劉貴忠, 王占輝, 王黎明. 基于多幀邊緣差異的視頻運動對象的分割與跟蹤算法[J]. 電子與信息學報, 2004, 26(5): 715-721.
Liu Long, Liu Gui-zhong, Wang Zhan-hui, Wang Li-ming. Segmentation and Tracking of Video Object of Interest Based on Change of Multi-frames Edge[J]. Journal of Electronics & Information Technology, 2004, 26(5): 715-721.
Citation: Liu Long, Liu Gui-zhong, Wang Zhan-hui, Wang Li-ming. Segmentation and Tracking of Video Object of Interest Based on Change of Multi-frames Edge[J]. Journal of Electronics & Information Technology, 2004, 26(5): 715-721.

基于多幀邊緣差異的視頻運動對象的分割與跟蹤算法

Segmentation and Tracking of Video Object of Interest Based on Change of Multi-frames Edge

  • 摘要: 從視頻場景中分割和跟蹤感興趣的視頻對象對于MPEG-4等基于對象的視頻編碼來說是關(guān)鍵性的技術(shù)之一。針對目前大部分視頻對象分割和追蹤算法相當復雜但仍不能有效地去除背景噪聲的問題,該文提出用于分割和跟蹤視頻運動對象的一種基于多幀邊緣差異的算法。該算法利用一組幀的邊緣差異來提取運動對象區(qū)域,通過聚類方法去除背景像素點,利用形態(tài)學算子得到對象分割模板,同時通過建立前幀感興趣對象與當前幀運動對象的幀間向量跟蹤當前幀的感興趣視頻對象。不同標準視頻測試序列的測試結(jié)果表明,該算法能夠?qū)崿F(xiàn)對感興趣的視頻運動對象更為精確、快速和有效地分割和跟蹤。
    Abstract: It is one of the key technologies to MPEG-4 grade codes based on target to segment and track the concerned video objects from the video scene. Most current seg-mentation and tracking algorithms are of high complexity but not effective in getting rid of background noise. One algorithm is put forward to segment and trace video objects based on edge difference among multiple frames. According to the proposed algorithm, edge difference between a group of frames is used to draw the area of moving objects; then, background pixels are removed through setting up pixel-measuring window and threshold value; the area of objects is set up by morphology operator; at the same time, vectors between the last concerned objects per frame and moving objects of present frame are established to follow current concerned objects. The result of various standard video test sequences shows that the proposed algorithm offers more accurate, faster and more effective segmentation and tracking of concerned video moving objects.
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  • Sikora T. The MPEG-4 video standard verification model[J].IEEE Trans. on Circuits and Systems for Video Technology.1997, 7(1):19-30[2]Marques F, Molina C. Object tracking for content-based functionalities, in SPIE Vis. Commun.Image Processing, 1997, vol. 3024: 190-199.[3]C. Gu, Lee M C. Semantic segmentation and tracking of semantic video objects. IEEE Trans.on Circuits and Systems for Video Technology, 1998, 8(5): 572-584.[4]C. Gu. Tracking of multiple semantic video objects for internet applications. SPIE, 1999, vol.3653:806-820,.[5]Thomas M, King N. Automatic segmentation of moving objects for video object plane generation[J].IEEE Trans. on Circuits and Systems for Video Technology.1998, 8(5):525-538[6]Mech R, Wollborn M. Automatic segmentation of movi ng objects (partial results of core experiment N2), ISO/IEC JTC1 /SC2 9/WG11 MPEG98/m3187, 1998.[7]Mech R, Wollborn M. A noise robust method for 2D shape estimation of moving objects in video sequences considering a moving camera[J].Signal Processing.1998, 66(2):203-217[8]Kim M.[J].Choi J G, Lee M H. Performance analysis of an ETRIs global motion compensation and scene cut detection algorithms for automatic segmentation. ISO/ IEC JTC1/SC29/WG11 MPEG97/m238.1997,:-[9]Bouthemy P, Francois E. Motion segmentation and qualitative dynamic scene analysis from an image sequence[J].Int. Journal of Computer Vision.1993, 10(2):157-182[10]Meyer F, Bouthemy P. Region-based tracking in an image sequence, in Proc.European Conf.Computer Vision (ECCV), Rennes, May 1992: 476-484.[11]Canny J F. A computational approach to edge detection. IEEE Trans. on PAMI, 1986, 6(3):679-698.
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出版歷程
  • 收稿日期:  2002-12-08
  • 修回日期:  2003-05-19
  • 刊出日期:  2004-05-19

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