基于对象的视频分割技术研究
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摘要
随着信息技术和计算机网络的飞速发展，多媒体信息已经成为人类获得信息的主要载体，而且日益丰富。海量数据要求必须提供高效的压缩和处理方法来对信息进行存储、传输和检索等各种处理。基于对象的视频处理技术是有效措施之一，视频对象分割是视频技术的基础而重要的工作，视频分割质量的好坏直接影响后期视频处理工作。
本文在阅读大量国内外最新文献以及对多种分割算法进行深入研究的基础上提出了一种快速有效的基于背景重构和变化检测的视频分割算法，该算法利用统计累积的方法得到包含遮挡域的完整背景信息，利用当前帧和所得到的背景图像相减得到视频对象，成功的克服了遮挡问题，在静止的背景条件下，对于单一运动目标能够得到比较准确的分割结果。
With the rapid development of information technology and Internet, multimedia has become the main media where people get information from. Abundant data force people to look for an efficient and high impact way to deal with so much information. Such as storing, transmitting and searching. Well, the technology of video object-based is one of important means. Video object segmentation is the base of video technology. The quality of segmentation will affect the subsequent work.
After reading a lot of the latest articles and researching all kinds of algorithms, I brought forward an auto segmentation algorithm based on rebuilding background and change detection in the article. It takes advantage of statistic and addition to get the integrated background. Then subtract the background from the current frame. It can get rid of the effect of shelter. We can get more accurate result by using this algorithm under the condition of still background and single motion object.
本文在阅读大量国内外最新文献以及对多种分割算法进行深入研究的基础上提出了一种快速有效的基于背景重构和变化检测的视频分割算法，该算法利用统计累积的方法得到包含遮挡域的完整背景信息，利用当前帧和所得到的背景图像相减得到视频对象，成功的克服了遮挡问题，在静止的背景条件下，对于单一运动目标能够得到比较准确的分割结果。
With the rapid development of information technology and Internet, multimedia has become the main media where people get information from. Abundant data force people to look for an efficient and high impact way to deal with so much information. Such as storing, transmitting and searching. Well, the technology of video object-based is one of important means. Video object segmentation is the base of video technology. The quality of segmentation will affect the subsequent work.
After reading a lot of the latest articles and researching all kinds of algorithms, I brought forward an auto segmentation algorithm based on rebuilding background and change detection in the article. It takes advantage of statistic and addition to get the integrated background. Then subtract the background from the current frame. It can get rid of the effect of shelter. We can get more accurate result by using this algorithm under the condition of still background and single motion object.
引文
1 李弼程 彭天强 彭波等．智能图像处理技术 北京：电子工业出版社，2004．7第二章
2 龚声蓉 刘纯平 王强等．数字图像处理与分析 北京：清华大学出版社 2006．7(7)168-169
3 MPEG-4 Group, "Information technology-coding of audio-visual objects: Visual" Doc. ISO/IEC JTC1/SC29/WG11 N2202, Final Committee Draft, 1998
4 Ner, S. Colonne, se, G. Russo and P Talone, Automatic moving object and background separation, Signal Processing, 1998, vol. 66, pp. 219-232
5 R. Mech and M. Wollborn, A noise robust method for segmentation of moving objects in video sequences, in Proceedings ICASSP '97(IEEE International Conference on Acoustics, Speech and Signal Processing), 1997, vol. 4, Munich, Germany, pp. 2657-2660
6 S. W. L. ee, J.G. Choi and S.D. Kim, Automatic segmentation of moving objects for video object plane generation, IEEE Transactions on Circuits and Systems for Video Technology, 1997, vol. 7, pp. 279-256
7 贾云得，机器视觉(第二版)北京：科学出版社 2002．5 pp235-238
8 Wang J. Y. A and Adelson E. H. Representing moving images with layers, IEEE Trans Image Processing, 1994, (3): 625-638.
9 Vucel Altunbasak P. Ethan Eren A. Murat Tekalp Region-based parametric motion segmentation using color information Graphical Models and Image Processing January 1998, Vol. 60 Issuel: 13-23
10 Wang V, Lee O. Active mesh: a feature seeking and tracking image sequence representation scheme. IEEE Trans Image Prco. 1994, (3):610-614
11 Murray D W, Buxton B F Scene segmentation from visual motion using global optimization. IEEE Trans Part Anal Mach Intel, 1987, 9(2): 220-228
12 Sethi I K, Jain R. Object-based estimation of dense motion fields. IEEE Trans. Image Processing, 1997, (6): 234-250
13 Diehl N. Object-oriented motion estimation and segmentation in image sequences. Signal Processing, 1988, 15(3): 315-334.
14 Choi JG, Lee S W, Kim S D. Spatio-temporal video segmentation using a joint similarity measure. Trans Circuits syst Video Technol, 1997, (3): 279-286
15 Mech R, Wolfborn M. Automatic segmentation of moving objects(partial resultsof core experiment N2). ISOIlEC JTC1/SC29/WGI1 MPEG98/M3187, 1998
16 Hotter M, Thoma R, Image segmentation based on object oriented mappinb parameter estimation. Signal Processing, 1988, 15(3): 315-334.
17 Kim M, Jeon J G, Kwak J, et aI. User's guide for a user-assisted video object segmentation ISO/IEC JTC1/SC291WG11 MPEG98/m3935, 1998.
18 Neri A, Colonnese S, Russo G. Video sequence segmentation for object-based coders using higher statistics. ISCAS'97, HONGKONG, 1997. 1.2.2
19 P Dufaux, J Konrad. Efficient, robust and fast global motion estimation for video coding [J] IEEE Trans Imaging Processing, 2002, 9(6) pp: 497-500
20 朱辉 面向对象生成的视频分割技术研究[博士学位论文]电子科技大学 2002．10(3)25-37 (8)100-110
21 杨高波 张兆扬 一种基于背景记录和变化检测的视频对象分割算法 上海大学学报 2003．4
22 王军 沙芸 吴裕树 基于背景模型的自动视频分割方法 计算机工程与应用 2004．9
23 包红强 基于内容的视频运动对象分割技术研究[博士学位论文] 上海：上海大学 2005．4(4)：55-56
24 袁基炜 史忠科 一种快速运动目标的背景提取算法 计算机应用研究2004
25 许志勇 平西建 沈海浪 一种基于变化区域检测的运动对象分割算法 信息工程大学学报 2004．6
26 魏冬梅 张之超 高振明 李海腾 一种基于背景的视频运动对象分割算法 山东大学学报 (理学版)2004．4
27 王成儒 顾广华 一种采用背景统计技术的视频对象分割算法 光电工程 2004．8
28 于跃龙 卢焕章 基于变化检测与时空滤波器的视频对象分割方法 计算机工程与科学 2006．3
29 苏大伟 周利莉 王继芳 基于背景重建和MDBP的视频对象分割算法 计算机工程与应用 2005
30 Meier T, Nagan K N. Automatic segmentation of moving object for video object plane generation [J]. IEEE Trans on Circuit and System for Video Technology, 1998, 8(5): 525-538.
31 于跃龙 视频语义信息提取关键技术研究[博士学位论文]长沙：国防科学技术大学 2005．4 (3)34-37
32 Adiv G Determining three-dimensional motion and structure from optical flow generated by several moving objects [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1985, 7(4), pp:384-401.
33 Bouthemy P Francois E. Motion segmentation and qualitative dynamic scene analysis from an image sequence [J]. International Journal on Computer Vision, 1993, 10(2), pp: 157-183.
34 Chang M M Sezan M I Tekalp A M. An algorithm for simultaneous motion estimation and scene segmentation [A]. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing [C], Adelaide, Australia, 1994, 5, pp:221-224.
35 Salembier P, Pandas M. Hierarchical morphological segmentation for image sequence coding [J]. IEEE Transactions on Image Processing, 1994, 3(5), pp: 639-651.
36 Choi J G, Lee W S, Kim S D. Spatio-temporal video segmentation using a joint similarity measure [J]. IEEE Transactions on Circuits and Systems for Video Technology, 1997, 7(2), pp: 279-286.
37 Kim Munchur, Kim Jinwoong. Moving video segmentation using statistical hypothesis testing [J]. Electronics Letters, 2000, Vol. 36, pp: 128-129.
2 龚声蓉 刘纯平 王强等．数字图像处理与分析 北京：清华大学出版社 2006．7(7)168-169
3 MPEG-4 Group, "Information technology-coding of audio-visual objects: Visual" Doc. ISO/IEC JTC1/SC29/WG11 N2202, Final Committee Draft, 1998
4 Ner, S. Colonne, se, G. Russo and P Talone, Automatic moving object and background separation, Signal Processing, 1998, vol. 66, pp. 219-232
5 R. Mech and M. Wollborn, A noise robust method for segmentation of moving objects in video sequences, in Proceedings ICASSP '97(IEEE International Conference on Acoustics, Speech and Signal Processing), 1997, vol. 4, Munich, Germany, pp. 2657-2660
6 S. W. L. ee, J.G. Choi and S.D. Kim, Automatic segmentation of moving objects for video object plane generation, IEEE Transactions on Circuits and Systems for Video Technology, 1997, vol. 7, pp. 279-256
7 贾云得，机器视觉(第二版)北京：科学出版社 2002．5 pp235-238
8 Wang J. Y. A and Adelson E. H. Representing moving images with layers, IEEE Trans Image Processing, 1994, (3): 625-638.
9 Vucel Altunbasak P. Ethan Eren A. Murat Tekalp Region-based parametric motion segmentation using color information Graphical Models and Image Processing January 1998, Vol. 60 Issuel: 13-23
10 Wang V, Lee O. Active mesh: a feature seeking and tracking image sequence representation scheme. IEEE Trans Image Prco. 1994, (3):610-614
11 Murray D W, Buxton B F Scene segmentation from visual motion using global optimization. IEEE Trans Part Anal Mach Intel, 1987, 9(2): 220-228
12 Sethi I K, Jain R. Object-based estimation of dense motion fields. IEEE Trans. Image Processing, 1997, (6): 234-250
13 Diehl N. Object-oriented motion estimation and segmentation in image sequences. Signal Processing, 1988, 15(3): 315-334.
14 Choi JG, Lee S W, Kim S D. Spatio-temporal video segmentation using a joint similarity measure. Trans Circuits syst Video Technol, 1997, (3): 279-286
15 Mech R, Wolfborn M. Automatic segmentation of moving objects(partial resultsof core experiment N2). ISOIlEC JTC1/SC29/WGI1 MPEG98/M3187, 1998
16 Hotter M, Thoma R, Image segmentation based on object oriented mappinb parameter estimation. Signal Processing, 1988, 15(3): 315-334.
17 Kim M, Jeon J G, Kwak J, et aI. User's guide for a user-assisted video object segmentation ISO/IEC JTC1/SC291WG11 MPEG98/m3935, 1998.
18 Neri A, Colonnese S, Russo G. Video sequence segmentation for object-based coders using higher statistics. ISCAS'97, HONGKONG, 1997. 1.2.2
19 P Dufaux, J Konrad. Efficient, robust and fast global motion estimation for video coding [J] IEEE Trans Imaging Processing, 2002, 9(6) pp: 497-500
20 朱辉 面向对象生成的视频分割技术研究[博士学位论文]电子科技大学 2002．10(3)25-37 (8)100-110
21 杨高波 张兆扬 一种基于背景记录和变化检测的视频对象分割算法 上海大学学报 2003．4
22 王军 沙芸 吴裕树 基于背景模型的自动视频分割方法 计算机工程与应用 2004．9
23 包红强 基于内容的视频运动对象分割技术研究[博士学位论文] 上海：上海大学 2005．4(4)：55-56
24 袁基炜 史忠科 一种快速运动目标的背景提取算法 计算机应用研究2004
25 许志勇 平西建 沈海浪 一种基于变化区域检测的运动对象分割算法 信息工程大学学报 2004．6
26 魏冬梅 张之超 高振明 李海腾 一种基于背景的视频运动对象分割算法 山东大学学报 (理学版)2004．4
27 王成儒 顾广华 一种采用背景统计技术的视频对象分割算法 光电工程 2004．8
28 于跃龙 卢焕章 基于变化检测与时空滤波器的视频对象分割方法 计算机工程与科学 2006．3
29 苏大伟 周利莉 王继芳 基于背景重建和MDBP的视频对象分割算法 计算机工程与应用 2005
30 Meier T, Nagan K N. Automatic segmentation of moving object for video object plane generation [J]. IEEE Trans on Circuit and System for Video Technology, 1998, 8(5): 525-538.
31 于跃龙 视频语义信息提取关键技术研究[博士学位论文]长沙：国防科学技术大学 2005．4 (3)34-37
32 Adiv G Determining three-dimensional motion and structure from optical flow generated by several moving objects [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1985, 7(4), pp:384-401.
33 Bouthemy P Francois E. Motion segmentation and qualitative dynamic scene analysis from an image sequence [J]. International Journal on Computer Vision, 1993, 10(2), pp: 157-183.
34 Chang M M Sezan M I Tekalp A M. An algorithm for simultaneous motion estimation and scene segmentation [A]. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing [C], Adelaide, Australia, 1994, 5, pp:221-224.
35 Salembier P, Pandas M. Hierarchical morphological segmentation for image sequence coding [J]. IEEE Transactions on Image Processing, 1994, 3(5), pp: 639-651.
36 Choi J G, Lee W S, Kim S D. Spatio-temporal video segmentation using a joint similarity measure [J]. IEEE Transactions on Circuits and Systems for Video Technology, 1997, 7(2), pp: 279-286.
37 Kim Munchur, Kim Jinwoong. Moving video segmentation using statistical hypothesis testing [J]. Electronics Letters, 2000, Vol. 36, pp: 128-129.