Optimal image and video closure by superpixel grouping

International Journal of Computer Vision

Volumn 100, Issue 1, 2012, Pages 99-119

  Levinshtein, Alex ^a   Sminchisescu, Cristian ^b   Dickinson, Sven ^a  

^a UNIVERSITY OF TORONTO   (Canada)

^b UNIVERSITY OF BONN   (Germany)

Author keywords

Closure; Figure ground segmentation; Motion segmentation; Perceptual grouping; Segmentation; Superpixels

Indexed keywords

CLOSED BOUNDARY; CLOSURE; COHERENT COMPONENTS; DETECTION APPROACH; EDGE SUPPORTS; MOTION SEGMENTATION; MULTISCALES; OPTIMAL IMAGES; OPTIMIZATION PROCEDURES; PERCEPTUAL GROUPING; SCENE ANALYSIS; SPATIAL COHERENCE; SPATIOTEMPORAL VOLUME; SUPERPIXELS;

GLOBAL OPTIMIZATION; IMAGE SEGMENTATION;

COST FUNCTIONS;

EID: 84863219761     PISSN: 09205691     EISSN: 15731405     Source Type: Journal    
DOI: 10.1007/s11263-012-0527-6     Document Type: Article

References (65)

1. Alpert, S., Galun, M., Basri, R., & Brandt, A. (2007). Image segmentation by probabilistic bottom-up aggregation and cue integration. In IEEE international conference on computer vision and pattern recognition.
2. Bascle, B., & Deriche, R. (1995). Region tracking through image sequences. In ICCV (p. 302).
3. M. Black A. Jepson 1998 Eigentracking: Robust matching and tracking of articulated objects using a view-based representation International Journal of Computer Vision 26 1 63 84 10.1023/A:1007939232436 (Pubitemid 128513060)
4. Borenstein, E., & Ullman, S. (2002). Class-specific, top-down segmentation. In European conference on computer vision (pp. 109-124).
5. Boykov, Y. Y., & Jolly, M. P. (2001). Interactive graph cuts for optimal boundary and region segmentation of objects in n-d images.
6. M. Brady H. Asada 1984 Smoothed local symmetries and their implementation The International Journal of Robotics Research 3 3 36 61 10.1177/ 027836498400300302 (Pubitemid 14661312)
7. Carreira, J., & Sminchisescu, C. (2010). Constrained parametric min-cuts for automatic object segmentation. In IEEE international conference on computer vision and pattern recognition.
8. Cham, T. J., & Cipolla, R. (1996). Geometric saliency of curve correspondences and grouping of symmetric contours. In European conference on computer vision (pp. 385-398). (Pubitemid 126064338)
9. D. Chung W. MacLean S. Dickinson 2006 Integrating region and boundary information for spatially coherent object tracking Image and Vision Computing 24 7 680 692 10.1016/j.imavis.2005.09.020 (Pubitemid 44163386)
10. D. Comaniciu V. Ramesh P. Meer 2003 Kernel-based object tracking IEEE Transactions on Pattern Analysis and Machine Intelligence 25 5 564 577 10.1109/TPAMI.2003.1195991
11. D. Cremers S. Soatto 2005 Motion competition: A variational approach to piecewise parametric motion segmentation International Journal of Computer Vision 62 3 10.1007/s11263-005-4882-4 (Pubitemid 40356777)
12. DeMenthon, D. (2002). Spatio-temporal segmentation of video by hierarchical mean shift analysis. In SMVP.
13. Y. Deng B. Manjunath 2001 Unsupervised segmentation of color-texture regions in images and video IEEE Transactions on Pattern Analysis and Machine Intelligence 23 800 810 10.1109/34.946985 (Pubitemid 32780009)
14. W. Dinkelbach 1967 On nonlinear fractional programming Management Science 13 492 498 242488 0152.18402 10.1287/mnsc.13.7.492
15. J. Elder S. Zucker 1994 A measure of closure Vision Research 34 3361 3369 10.1016/0042-6989(94)90070-1 (Pubitemid 24338432)
16. Elder, J. H., & Zucker, S. W. (1996). Computing contour closure. In European conference on computer vision (pp. 399-412). (Pubitemid 126064339)
17. Endres, I., & Hoiem, D. (2010). Category independent object proposals. In ECCV (pp. 575-588).
18. Estrada, F. J., & Jepson, A. D. (2004). Perceptual grouping for contour extraction. In IEEE international conference on pattern recognition (pp. 32-35).
19. Estrada, F. J., & Jepson, A. D. (2006). Robust boundary detection with adaptive grouping. In Computer vision and pattern recognition workshop (p. 184).
20. Fowlkes, C., Belongie, S., & Malik, J. (2001). Efficient spatiotemporal grouping using the Nyström method. In CVPR (pp. 231-238).
21. M. Gelgon P. Bouthemy 2000 A region-level motion-based graph representation and labeling for tracking a spatial image partition Pattern Recognition 33 4 725 740 10.1016/S0031-3203(99)00083-7 (Pubitemid 30553120)
22. H. Greenspan J. Goldberger A. Mayer 2004 Probabilistic space-time video modeling via piecewise gmm IEEE Transactions on Pattern Analysis and Machine Intelligence 26 3 384 396 10.1109/TPAMI.2004.1262334
23. Huang, Y., Liu, Q., & Metaxas, D. (2009). Video object segmentation by hypergraph cut. In IEEE international conference on computer vision and pattern recognition (pp. 1738-1745).
24. M. Isard A. Blake 1998 Condensation-conditional density propagation for visual tracking International Journal of Computer Vision 29 5 28 10.1023/A:1008078328650 (Pubitemid 128523364)
25. D. Jacobs 1996 Robust and efficient detection of salient convex groups IEEE Transactions on Pattern Analysis and Machine Intelligence 18 1 23 37 2418761 10.1109/34.476008 (Pubitemid 126772788)
26. Jepson, A. D., Fleet, D. J., & Black, M. J. (2002). A layered motion representation with occlusion and compact spatial support. In ECCV (pp. 692-706).
27. I. Jermyn H. Ishikawa 2001 Globally optimal regions and boundaries as minimum ratio weight cycles IEEE Transactions on Pattern Analysis and Machine Intelligence 23 1075 1088 10.1109/34.954599 (Pubitemid 33047947)
28. Jojic, N., & Frey, B. J. (2001). Learning flexible sprites in video layers. In CVPR (Vol. 1, p. 199).
29. Kolmogorov, V., Boykov, Y., & Rother, C. (2007). Applications of parametric maxflow in computer vision. In IEEE international conference on computer vision (pp. 1-8).
30. Lempitsky, V., Kohli, P., Rother, C., & Sharp, T. (2009). Image segmentation with a bounding box prior.
31. Levinshtein, A., Sminchisescu, C., & Dickinson, S. (2009a). Multiscale symmetric part detection and grouping (pp. 2162-2169).
32. A. Levinshtein A. Stere K. N. Kutulakos D. J. Fleet S. J. Dickinson K. Siddiqi 2009 Turbopixels: Fast superpixels using geometric flows IEEE Transactions on Pattern Analysis and Machine Intelligence 31 12 2290 2297 10.1109/TPAMI.2009.96
33. Levinshtein, A., Sminchisescu, C., & Dickinson, S. (2010a). Optimal contour closure by superpixel grouping. In ECCV (pp. 480-493).
34. Levinshtein, A., Sminchisescu, C., & Dickinson, S. (2010b). Spatiotemporal closure. In ACCV (pp. 369-382).
35. Li, F., Carreira, J., & Sminchisescu, C. (2010). Object recognition as ranking holistic figure-ground hypotheses. In CVPR.
36. Lowe, D. G. (1985). Perceptual organization and visual recognition. Norwell: Kluwer Academic.
37. Lucas, B. D., & Kanade, T. (1981). An iterative image registration technique with an application to stereo vision. In Proceedings of imaging understanding workshop (pp. 674-679). (Pubitemid 14478744)
38. Maire, M., Arbelaez, P., Fowlkes, C., & Malik, J. (2008). Using contours to detect and localize junctions in natural images. In IEEE international conference on computer vision and pattern recognition.
39. D. R. Martin C. C. Fowlkes J. Malik 2004 Learning to detect natural image boundaries using local brightness, color, and texture cues IEEE Transactions on Pattern Analysis and Machine Intelligence 26 530 549 10.1109/TPAMI.2004.1273918
40. Megret, R., & DeMenthon, D. (2002). A survey of spatio-temporal grouping techniques (Tech. rep.). University of Maryland, College Park.
41. Mori, G., Ren, X., Efros, A. A., & Malik, J. (2004). Recovering human body configurations: Combining segmentation and recognition. In IEEE international conference on computer vision and pattern recognition (pp. 326-333).
42. F. Moscheni S. Bhattacharjee M. Kunt 1998 Spatiotemporal segmentation based on region merging IEEE Transactions on Pattern Analysis and Machine Intelligence 20 9 897 915 10.1109/34.713358 (Pubitemid 128741354)
43. N. Paragios R. Deriche 2000 Geodesic active contours and level sets for the detection and tracking of moving objects IEEE Transactions on Pattern Analysis and Machine Intelligence 22 3 266 280 10.1109/34.841758
44. I. Patras R. L. Lagendijk E. A. Hendriks 2001 Video segmentation by map labeling of watershed segments IEEE Transactions on Pattern Analysis and Machine Intelligence 23 3 326 332 10.1109/34.910886 (Pubitemid 32286639)
45. Y. Pritch A. Rav-Acha S. Peleg 2008 Nonchronological video synopsis and indexing IEEE Transactions on Pattern Analysis and Machine Intelligence 30 1971 1984 10.1109/TPAMI.2008.29
46. Ren, X., Fowlkes, C. C., & Malik, J. (2005a). Cue integration in figure/ground labeling. In Advances in neural information processing systems.
47. Ren, X., Fowlkes, C. C., & Malik, J. (2005b). Scale-invariant contour completion using conditional random fields. In IEEE international conference on computer vision (Vol. 2, pp. 1214-1221). (Pubitemid 44042319)
48. C. Rother V. Kolmogorov A. Blake 2004 "grabcut": interactive foreground extraction using iterated graph cuts SIGGRAPH 23 3 309 314 10.1145/1015706.1015720 (Pubitemid 40163720)
49. P. Saint-Marc H. Rom G. Medioni 1993 B-spline contour representation and symmetry detection IEEE Transactions on Pattern Analysis and Machine Intelligence 15 11 1191 1197 10.1109/34.244680
50. Shi, J., & Malik, J. (1998). Motion segmentation and tracking using normalized cuts. In ICCV (p. 1154).
51. J. Shi J. Malik 2000 Normalized cuts and image segmentation IEEE Transactions on Pattern Analysis and Machine Intelligence 22 8 888 905 10.1109/34.868688
52. J. Stahl S. Wang 2007 Edge grouping combining boundary and region information IEEE Transactions on Image Processing 16 10 2590 2606 2467788 10.1109/TIP.2007.904463 (Pubitemid 47456025)
53. J. Stahl S. Wang 2008 Globally optimal grouping for symmetric closed boundaries by combining boundary and region information IEEE Transactions on Pattern Analysis and Machine Intelligence 30 3 395 411 10.1109/TPAMI.2007.1186 (Pubitemid 351280048)
54. Stein, A., Hoiem, D., & Hebert, M. (2007). Learning to find object boundaries using motion cues. In IEEE international conference on computer vision (pp. 1-8).
55. D. Wang 1998 Unsupervised video segmentation based on watersheds and temporal tracking IEEE Transactions on Circuits and Systems for Video Technology 8 5 539 546 10.1109/76.718501 (Pubitemid 128743721)
56. J. Wang E. Adelson 1994 Representing moving images with layers IEEE Transactions on Image Processing 3 5 625 638 10.1109/83.334981
57. S. Wang T. Kubota J. Siskind J. Wang 2005 Salient closed boundary extraction with ratio contour IEEE Transactions on Pattern Analysis and Machine Intelligence 27 4 546 561 10.1109/TPAMI.2005.84 (Pubitemid 40556110)
58. Weiss, Y. (1997). Smoothness in layers: Motion segmentation using nonparametric mixture estimation. In CVPR (p. 520).
59. Weiss, Y., & Adelson, E. H. (1996). A unified mixture framework for motion segmentation: Incorporating spatial coherence and estimating the number of models. In CVPR (p. 321).
60. Welch, G., & Bishop, G. (1995). An introduction to the Kalman filter (Tech. rep.).
61. Wertheimer, M. (1938). Laws of organization in perceptual forms. In W. Ellis (ed.), Source book of gestalt psychology. New York: Harcourt, Brace.
62. L. R. Williams A. R. Hanson 1996 Perceptual completion of occluded surfaces Computer Vision and Image Understanding 64 1 1 20 10.1006/cviu.1996. 0043
63. Williams, L. R., & Jacobs, D. W. (1995). Stochastic completion fields: a neural model of illusory contour shape and salience. In IEEE international conference on computer vision (p. 408).
64. A. Ylä-Jääski F. Ade 1996 Grouping symmetrical structures for object segmentation and description Computer Vision and Image Understanding 63 3 399 417 10.1006/cviu.1996.0031 (Pubitemid 126405177)
65. Zhu, Q., Song, G., & Shi, J. (2007). Untangling cycles for contour grouping. In IEEE international conference on computer vision.