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Automatic Segmentation of Moving Objects in Video Sequences for Indoor and Outdoor Applications 被引量:1

Automatic Segmentation of Moving Objects in Video Sequences for Indoor and Outdoor Applications
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摘要 Computer vision systems have an impressive spread both for their practicalapplication and for theoretical research . The common approach used in such systems consists of agood segmentation of moving objects from video sequences . This paper presents an automaticalgorithm for segmenting and extracting moving objects suitable for indoor and outdoor videoapplications, where the background scene can be captured beforehand . Since edge detection is oftenused to extract accurate boundaries of the image's objects, the first step in our algorithm isaccomplished by combining two edge maps which are detected from the frame difference in twoconsecutive frames and the background subtraction . After removing edge points that belong to thebackground, the resulting moving edge map is fed to the object extraction step . A fundamental taskin this step is to declare the candidates of the moving object, followed by applying morphologicaloperations. The algorithm is implemented on a real video sequence as well as MPEG- 4 sequence andgood segmentation results are achieved. Computer vision systems have an impressive spread both for their practicalapplication and for theoretical research . The common approach used in such systems consists of agood segmentation of moving objects from video sequences . This paper presents an automaticalgorithm for segmenting and extracting moving objects suitable for indoor and outdoor videoapplications, where the background scene can be captured beforehand . Since edge detection is oftenused to extract accurate boundaries of the image's objects, the first step in our algorithm isaccomplished by combining two edge maps which are detected from the frame difference in twoconsecutive frames and the background subtraction . After removing edge points that belong to thebackground, the resulting moving edge map is fed to the object extraction step . A fundamental taskin this step is to declare the candidates of the moving object, followed by applying morphologicaloperations. The algorithm is implemented on a real video sequence as well as MPEG- 4 sequence andgood segmentation results are achieved.
出处 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2003年第4期76-81,共6页 中国邮电高校学报(英文版)
关键词 frame difference background subtraction moving object segmentation cannyedge detection morphological operation frame difference background subtraction moving object segmentation cannyedge detection morphological operation
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参考文献15

  • 1HARITAOGLU I, HARWOOD D, DAVIS L S. W4:Real-time surveillance of people and their activities[J].IEEE Trans on Pattern Anal Machine Intell, 2000, 22(8): 809 - 830.
  • 2KIMJB, PARK HS, PARK M H, et al. Unsupervised moving object segmentation and recognition using clustering and a neural network[A]. Proc IJCNN'02,Vol 2[C]. Piscataway, NJ: IEEE, 2002. 1240-1245.
  • 3OHTA N. A statistical approach to background subtraction for surveillance systems[A]. Proc ICCV Computer Vision, Vol 2[C]. Los Alamitos, CA: IEEE Comput Soc, 2001. 481 - 486.
  • 4LIN C, CHANG Y, CHEN Y, SUN M. Implementation of a realtime object-based virtual meeting system[A]. Proc IEEE Int Conf Multimedia and Expo[C].Tokyo, Japan: 2001. 565-568.
  • 5NERI A, COLONNESE, RUSSO G, et al. Automatic moving object and background separation [ J ]. Signal Processing, 1998, 66(2) : 219-232.
  • 6MEIER T, NGAN K N. Automatic segmentation of moving objects for video object plane generation [J].IEEE Trans on Circuits Syst Video Technol, 1998, 8(5) : 525-538.
  • 7CASTAGNO R, EBRAHIMI T, KUNT M. Video segmentation based on multiple features for interactive multimedia applications [J ]. IEEE Trans on Circuits Syst Video Technol, 1998, 8(5) : 562-571.
  • 8GU C, LEE M. Semiautomatic segmentation and tracking of semantic video objects[J]. IEEE Trans on Circuits Syst Video Technol, 1998, 8(5) : 572 - 584.
  • 9KIM M, CHOI J G, KIM D, et al. A VOP generation tool: Automatic segmentation of moving objects in image sequences based on spatio-temporal information[J].IEEE Trans on Circuits Syst Video Technol, 1999, 9(8) : 1216-1226.
  • 10CHIEN S, MA S, CHEN L. Efficient moving object segmentation algorithm using background registration technique[J ]. IEEE Trans on Circuits Syst Video Technol, 2002, 12(7) : 577-586.

同被引文献12

  • 1MCCANE B,NOVINS K,CRANNITCH D,et al.On Benchmarking Optical Flow[J].Computer Vision and Image Understanding,2001,84 (1):126-143.
  • 2SONG S MOON-HO,KWON TAE-HOON.On Detection of Gradual Scene Changes for Parsing of Video Data[ C ] // Proceedings of SPIE,Storage And Retrieval for Image and Video Databases.San Jose,CA,USA:SPIE,1997,3312:404-409.
  • 3KOPRINSKAL I,CARRATO S.Tmporal Video Segmentation:A Survey[C] //Signal Processing:Image Communication,2001,16 (5):477-500.
  • 4SETCHELL C J,CAMPBE llN W.Using Colour Gabor Texture Features for Scene Understanding[ C] //7th International Conference on Image Processing and Its Applications,Institution of Electrical Engineers.Manchester,United Kingdom:[ s.n],1999:372-376.
  • 5TOURAPIS A M.ISO/IEC JTCl/S C29/WGl1 MPEG2000/M5867 (2000),Core Experiment on Block Based Motion Estimation[ S].
  • 6TOURAPIS A M,AU O C,LION M L,et al.In ISO/IEC JTCl/S C29/WG11 MPEG2000/m5866 (2000),Fast Block Matching Motion Estimation Using Predictive Motion Vector Field Adaptive Search Technique (PMVFAST)[ S].
  • 7ZHU S,MA K K.A New Diamond Search Algorithm for Fast Block-Matching Motion Estimation[J].IEEE Trans Image Processing,2000,9:287-290.
  • 8PO LAI-MAN,MA WING-CHUNG.A Novel Four-Step Search Algorithm for Fast Block Motion Estimation[ J ].IEEE Trans Circuits Syst Video Technol,1996,6 (3):313-317.
  • 9沈会良,李志能.基于矩和小波变换的数字、字母字符识别研究[J].中国图象图形学报(A辑),2000,5(3):249-252. 被引量:36
  • 10金红,周源华.基于内容检索的视频处理技术[J].中国图象图形学报(A辑),2000,5(4):276-283. 被引量:38

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