期刊文献+

结合视频分割的形状编码算法

Shape coding algorithm integrated video segmentation
下载PDF
导出
摘要 设计了结合视频分割的形状编码新算法。该算法采用提出的基于柔性初始轮廓的水平集(levelset)运动对象分割算法得到零水平集,即对象的形状轮廓,然后进一步采用提出的基于边界与采样轮廓一致性的基准线编码方法直接得到视频对象的形状编码,从而避免了采用二值矩阵提取形状轮廓产生的误差和时间花费,有效地节约了码流,具有了较好的编码效果。 Baseline-based shape coding algorithm and image-dependent shape coding were researched. By integrating the two methods, a new shape coding algorithm was designed. The video object is segmented based on level set method firstly, and the result called zero level set is coded by the baseline-based coding. The new algorithm can overcome effec- tively the lacks of the baseline-based shape coding algorithm and image-dependent shape coding. The experimental results have demonstrated that the new algorithm is more effective and suitable for real application.
出处 《通信学报》 EI CSCD 北大核心 2008年第3期70-75,共6页 Journal on Communications
基金 国家自然科学基金资助项目(60673092) 教育部科研重点基金资助项目(205059) 江苏省高校自然科学基金资助项目(07KJD520186)~~
关键词 形状编码 视频分割 水平集 基准线 shape coding video segmentation level set baseline
  • 相关文献

参考文献11

  • 1徐凌云.MPEG-4形状编码技术[J].通信技术,2001,34(2):37-38. 被引量:1
  • 2PAULO N, FERRAN M, FERNANDO P, et al. A contour-based approach to binary shape coding using a multiple grid chain code[J]. Signal Processing Image Communication, 2000, 15(7): 585-599.
  • 3CHUNG J W, LEE J H, MOON J H, et al. A new vertex-based binary shape codex for high coding efficiency[J]. Signal Processing Image Communication, 2000, 15(7): 665-684.
  • 4LUO H T. Image-dependent shape coding and representation[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2005,15 (3): 345-354.
  • 5LEE S H, CHO D S. Binary shape coding using baseline-based method[J]. IEEE Transactions on Circuits and Systems for Video Technology, 1999,9(1):44-58.
  • 6MEIER T, NGAN K N. Automatic segmentation of moving objects for video object plane generation[J]. IEEE Transactions on Circuits and Systems for Video Technology, 1998, 8(5):525-538.
  • 7NGUYEN H T, WORRING M, DEV A. Detection of moving objects in video using a robust motion similarity measure[J]. IEEE Transactions on Image Processing, 2000, 10( 1): 137 - 141.
  • 8BORS A G, PITAS I. Prediction and tracking of moving objects in image sequence[J]. IEEE Transactions on Image Processing, 2000, 9(8): 1441-1445.
  • 9LI L Y, MAYLOR K, LEUNG H. Integrating intensity and texture differences for robust change detection[J]. IEEE Transactions on Image Processing, 2002, 11(2): 105-112.
  • 10杨莉,杨新.基于水平集方法的多运动目标分割[J].上海交通大学学报,2004,38(5):713-717. 被引量:4

二级参考文献14

  • 1Rosin P.Thresholdirg for change detection[A].Proceedings of the IEEE International Conference on Computer Vision [C].Bombay,India:ICCV,1998.274-279.
  • 2Caselles V,Kimmel R,Spairo G.Geodesic active contours [J].International Journal of Computer Vision,1997,22(1):61- 79.
  • 3Malladi R,Serbian J A,Vemuri B C.Shape modeling with front propagation:a level set approach[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1995,17 (2):158- 175.
  • 4Chan T F,Vese L A.Active contours without edges [J].IEEE Transactions on Image Processing,2001,10(2):266- 277.
  • 5Kornprobst P,Deriche R,Aubert G.Image sequence analysis via partial differential equations[J].Journal of Mathematical Imaging and Vision,1999,11:5-26.
  • 6Elgammal A,Harwood D,Davis L.Non-parametric model for background subtraction [A].Proceedings of European Conference on Computer Vision [C].Dublin,Ireland :ECCV,2000.751 - 767.
  • 7Besson S J,Barlaud M,Aubert G.Video object segmentation using Eulerian region-based active contours [A].Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition[C].Vancouver,Canada:ICCV,2001.353 -360.
  • 8Stauffer C,Grimson E.Learning patterns of activity using real-time tracking [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22(8):747-757.
  • 9Jung Y K,Lee K W,Ho Y S.Content-based event retrieval using semantic scene interpretation for automated traffic surveillance[J].IEEE Transactions on Intelligent Transportation Systems,2001,2 (3) :151 -163.
  • 10Li L Y,Leung M K H.Integrating intensity and texture differences for robust change detection [J ].IEEE Transactions on Image Processing,2002,11(2):105-112.

共引文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部