A geometric approach to joint 2D region-based segmentation and 3D pose estimation using a 3D shape prior

SIAM Journal on Imaging Sciences

Volumn 3, Issue 1, 2010, Pages 110-132

  Dambreville, Samuel ^a   Sandhu, Romeil ^a   Yezzi, Anthony ^a   Tannenbaum, Allen ^a  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Differential geometry; Region based segmentation and tracking; Three dimensional pose estimation; Three dimensional shape prior; Variational methods

Indexed keywords

DIFFERENTIAL GEOMETRY; POSE ESTIMATION; REGION-BASED SEGMENTATION; THREE-DIMENSIONAL SHAPE; VARIATIONAL METHODS;

D REGION; ESTIMATION; GEOMETRY; GESTURE RECOGNITION; IMAGE SEGMENTATION; OBJECT RECOGNITION; SHAPE OPTIMIZATION; TRACKING (POSITION); TWO DIMENSIONAL;

THREE DIMENSIONAL;

EID: 78651581975     PISSN: None     EISSN: 19364954     Source Type: Journal    
DOI: 10.1137/080741653     Document Type: Article

References (40)

1. L. Quan and Z.-D. Lan, Linear n-point camera pose determination, IEEE Trans. Pattern Anal. Mach.Intell., 21 (1999), pp. 774-780.
2. M. Dhome, M. Richetin, and J.-T. Lapreste, Determination of the attitude of 3D objects from asingle perspective view, IEEE Trans. Pattern Anal. Mach. Intell., 11 (1989), pp. 1265-1278.
3. E. Marchand, P. Bouthemy, and F. Chaumette, A 2D-3D model-based approach to real-time visualtracking, Image Vision Comput., 19 (2001), pp. 941-955.
4. M. Zerroug and R. Nevatia, Pose estimation of multi-part curved objects, in Proceedings of theInternational Symposium on Computer Vision (ISCV '95), 1995, p. 431.
5. B. Rosenhahn, C. Perwass, and G. Sommer, Pose estimation of free-form contours, Int. J. Comput.Vision, 62 (2005), pp. 267-289.
6. T. Drummond and R. Cipolla, Real-time tracking of multiple articulated structures in multiple views,in Proceedings of the 6th European Conference on Computer Vision (ECCV), 2000, pp. 20-36.
7. V. Caselles, R. Kimmel, and G. Sapiro, Geodesic active contours, Int. J. Comput. Vision, 22 (1997),pp. 61-79.
8. S. Kichenassamy, S. Kumar, P. Olver, A. Tannenbaum, and A. Yezzi, Conformal curvature flow:From phase transitions to active vision, Arch. Rational Mech. Anal., 134 (1996), pp. 275-301.
9. S. Chun Zhu and A. L. Yuille, Region competition: Unifying snakes, region growing, and Bayes/MDLfor multiband image segmentation, IEEE Trans. Pattern Anal. Mach. Intell., 18 (1996), pp. 884-900.
10. T. Chan and L. Vese, Active contours without edges, IEEE Trans. Image Process., 10 (2001), pp.266-277.
11. N. Paragios and R. Deriche, Geodesic active regions: A new paradigm to deal with frame partitionproblems in computer vision, J. Vis. Commun. Image Represent., 13 (2002), pp. 249-268.
12. S. Dambreville, A. Yezzi, M. Niethammer, and A. Tannenbaum, A variational framework combininglevel-sets and thresholding, in proceedings of the British Machine Vision Conference (BMVC),2007, pp. 266-280.
13. O. Michailovich, Y. Rathi, and A. Tannenbaum, Image segmentation using active contours drivenby the Bhattacharyya gradient flow, IEEE Trans. Image Process., 16 (2007), pp. 2787-2801.
14. J. Kim, J. Fisher, A. Yezzi, M. Cetin, and A. Willsky, Nonparametric methods for image segmentationusing information theory and curve evolution, in Proceedings of the 2002 IEEE InternationalConference on Image Processing (ICIP), Vol. 3, 2002, pp. 797-800.
15. M. Rousson and D. Cremers, Efficient kernel density estimation of shape and intensity priors for levelset segmentation, in Procceedings of the International Conference on Medical Image Computing andComputer Assisted Intervention (MICCAI), Vol. 2, Springer-Verlag, Berlin, Heidelberg, 2005, pp.757-764.
16. N. Paragios and R. Deriche, Geodesic active regions for supervised texture segmentation, in Proceedingsof the IEEE International Conference on Computer Vision (ICCV), Vol. 2, 1999, pp. 926-932.
17. M. Leventon, E. Grimson, and O. Faugeras, Statistical shape influence in geodesic active contours, inProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition(CVPR), 2000, pp. 316-323.
18. A. Tsai, T. Yezzi, W. Wells, C. Tempany, D. Tucker, A. Fan, E. Grimson, and A. Willsky,A shape-based approach to the segmentation of medical imagery using level sets, IEEE Trans. Med.Imaging, 22 (2003), pp. 137-153.
19. D. Cremers, T. Kohlberger, and C. Schnoerr, Shape statistics in kernel space for variational imagesegmentation, Pattern Recognition, 36 (2003), pp. 1929-1943.
20. S. Dambreville, Y. Rathi, and A. Tannenbaum, Shape-based approach to robust image segmentationusing kernel PCA, in Proceedings of the IEEE Conference on Computer Vision and PatternRecognition, 2006, pp. 977-984.
21. S. Osher and R. Fedkiw, Level Set Methods and Dynamic Implicit Surfaces, Springer-Verlag, NewYork, 2003.
22. G. Turk and M. Levoy, Zippered polygon meshes from range images, in Proceedings of SIGGRAPH,ACM, New York, 1994, pp. 311-318.
23. A. Yezzi and S. Soatto, Structure from motion for scenes without features, in Proceedings of the IEEEComputer Society Conference on Computer Vision and Pattern Recognition (CVPR), Vol. 1, 2003,pp. 171-178.
24. S. Dambreville, R. Sandhu, A. Yezzi, and A. Tannenbaum, Robust 3D pose estimation and efficient2D region-based segmentation from a 3D shape prior, in Proceedings of the European Conference onComputer Vision (ECCV), 2008, pp. 169-182.
25. O. D. Faugeras and R. Keriven, Variational principles, surface evolution PDEs, level set methods,and the stereo problem, IEEE Trans. Image Process., 7 (1998), pp. 336-344.
26. A. Yezzi and S. Soatto, Stereoscopic segmentation, Int. J. Comput. Vision, 53 (2003), pp. 31-43.
27. G. Unal, A. Yezzi, S. Soatto, and G. Slabaugh, A variational approach to problems in calibrationof multiple cameras, IEEE Trans. Pattern Anal. Mach. Intell., 29 (2007), pp. 1322-1338.
28. T. Riklin-Raviv, N. Kiryati, and N. Sochen, Exploiting occluding contours for real-time 3D tracking:A unified approach, in Proceedings of the IEEE International Conference on Computer Vision (ICCV),Vol. 1, 2005, pp. 204-211.
29. B. Rosenhahn, T. Brox, and J. Weickert, Three-dimensional shape knowledge for joint image segmentationand pose tracking, Int. J. Comput. Vision, 73 (2007), pp. 243-262.
30. C. Schmaltz, B. Rosenhahn, T. Brox, D. Cremers, J. Weickert, L. Wietzke, and G. Sommer,Region-based pose tracking, in Pattern Recognition and Image Analysis, Lecture Notes in Comput.Sci. 4478, Springer-Verlag, Berlin, 2007, pp. 56-63.
31. M. P. DoCarmo, Differential Geometry of Curves and Surfaces, Prentice-Hall, Englewood Cliffs, NJ,1976.
32. M. Bray, P. Kohli, and P. Torr, Posecut: Simultaneous segmentation and 3D pose estimation ofhumans using dynamic graph-cuts, in Procceedings of the European Conference on Computer Vision(ECCV), Vol. 2, 2006, pp. 642-655.
33. P. Kohli, J. Rihan, M. Bray, and P. Torr, Simultaneous segmentation and pose estimation of humansusing dynamic graph cuts, Int. J. Comput. Vision, 79 (2008), pp. 285-298.
34. V. Lepetit and P. Fua, Monocular model-based 3D tracking of rigid objects: A survey, Found. TrendsComput. Graph. Vis., 1 (2005), pp. 1-89.
35. G. Li, Y. Tsin, and Y. Genc, Exploiting occluding contours for real-time 3D tracking: A unifiedapproach, in Proceedings of the IEEE Conference on Computer Vision (ICCV), 2007, pp. 1-8.
36. D. Forsyth and J. Ponce, Computer Vision: A Modern Approach, Prentice-Hall, Englewood Cliffs,NJ, 2003.
37. R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge UniversityPress, Cambridge, UK, 2000.
38. Y. Ma, S. Soatto, J. Kosecka, and S. Sastry, An Invitation to 3D Vision, Springer-Verlag, NewYork, 2005.
39. M. Rousson and R. Deriche, A variational framework for active and adaptative segmentation of vectorvalued images, in Proceedings of the Workshop on Motion and Video Computing, IEEE ComputerSociety, Washington, DC, 2002.
40. R. C. Gonzalez and R. E. Woods, Digital Image Processing, 3rd ed., Prentice-Hall, Upper SaddleRiver, NJ, 2008.