Image and video segmentation by anisotropic kernel mean shift

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3022, Issue , 2004, Pages 238-249

  Wang, Jue ^a   Thiesson, Bo ^a   Xu, Yingqing ^a   Cohen, Michael ^a  

^a MICROSOFT RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANISOTROPY; COMPUTER VISION;

ANISOTROPIC KERNEL; IMAGE AND VIDEO SEGMENTATION; INITIAL PARAMETER; LOCAL STRUCTURE; LOCAL-DENSITY; NONPARAMETRIC ESTIMATORS; RADIALLY SYMMETRIC; SIMPLE HEURISTICS;

IMAGE SEGMENTATION;

EID: 35048841307     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-24671-8_19     Document Type: Article

References (13)

1. Comaniciu, D., Meer, P.: Mean shift analysis and applications. Proc. IEEE Int. Conf. on Computer Vision, Greece (1999) 1197-1203.
2. Comaniciu, D., Ramesh, V., Meer, P.: Real-time tracking of non-rigid objects using mean shift. Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition (2000) 142-151.
3. DeMenthon, D., Megret, R.: The variable bandwidth mean shift and data-driven scale selection. Proc. IEEE 8th Int. Conf. on Computer Vision, Canada (2001) 438-445.
4. Comaniciu, D.: An Algorithm for Data-Driven Bandwidth Selection. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 25, No. 2, February 2003 (2003).
5. Comaniciu, D., Meer, P.: Mean shift: a robust approach toward feature space analysis. IEEE Trans. on PAMI (2002) 603-619.
6. DeMenthon, D., Megret, R.: Spatio-temporal segmentation of video by hierarchical mean shift analysis. Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition (2000) 142-151.
7. Fukunaga, K., Hostetler, L.: The estimation of the gradient of a density function, with applications in pattern recognition. IEEE Trans. Information Theory 21 (1975) 32-40.
8. Lorensen, W.E., Cline, H.E.: Marching Cubes: a high resolution 3D surface reconstruction algorithm. Proc. ACM SIGGRAPH 1987, (1987) 163-169.
9. Megret, R., DeMenthon, D.: A Survey of Spatio-Temporal Grouping Techniques. Technical report: LAMP-TR-094/CS-TR-4403, University of Maryland, College Park (1994).
10. Pal, N.R., Pal, S.K.: A review on image segmentation techniques. Pattern Recognition 26 9 (1993) 1277-1294.
11. Skarbek, W., Koschan, A.: Colour Image Segmentation: A survey. Technical report, Technical University Berlin (1994).
12. Singh, M., Ahuja, N.: Regression Based Bandwidth Selection for Segmentation using Parzen Windows. Proc. IEEE International Conference on Computer Vision (2003) 1 2-9.
13. Wand, M., Joncs, M.: Kernel Smoothing. Chapman & Hall (1995) p. 95.