A benchmark dataset and evaluation methodology for video object segmentation

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 2016-December, Issue , 2016, Pages 724-732

  Perazzi, F ^a,b   Pont Tuset, J ^a   McWilliams, B ^b   Gool, L Van ^a   Gross, M ^a,b   Sorkine Hornung, A ^b  

^a ETH ZURICH   (Switzerland)

^b DISNEY RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; MOTION COMPENSATION; PATTERN RECOGNITION;

ALGORITHM PERFORMANCE; BENCHMARK DATASETS; COMPREHENSIVE ANALYSIS; EVALUATION METHODOLOGIES; HIGH QUALITY DATA; TEMPORAL COHERENCE; VIDEO SEGMENTATION; VIDEO-OBJECT SEGMENTATION;

IMAGE SEGMENTATION;

EID: 84986253571     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2016.85     Document Type: Conference Paper

References (53)

1. V. Badrinarayanan, F. Galasso, and R. Cipolla. Label propagation in video sequences. In CVPR, 2010.
2. X. Bai, J. Wang, D. Simons, and G. Sapiro. Video snapcut: robust video object cutout using localized classifiers. ACM Trans. Graph., 28 (3), 2009.
3. S. Belongie, J. Malik, and J. Puzicha. Shape matching and object recognition using shape contexts. TPAMI, 24 (4), 2002.
4. G. J. Brostow, J. Fauqueur, and R. Cipolla. Semantic object classes in video: A high-definition ground truth database. Pattern Recognition Letters, 30 (2), 2009.
5. T. Brox and J. Malik. Object segmentation by long term analysis of point trajectories. In ECCV, 2010.
6. D. J. Butler, J. Wulff, G. B. Stanley, and M. J. Black. A naturalistic open source movie for optical flow evaluation. In ECCV, 2012.
7. J. Chang, D. Wei, and J. W. F. III. A video representation using temporal superpixels. In CVPR, 2013.
8. A. Y. C. Chen and J. J. Corso. Propagating multi-class pixel labels throughout video frames. In WNYIPW, 2010.
9. R. Collins, X. Zhou, and S. K. Teh. An open source tracking testbed and evaluation web site. In PETS 2005, January 2005.
10. G. Csurka, D. Larlus, and F. Perronnin. What is a good evaluation measure for semantic segmentation In BMVC, 2013.
11. P. Dollár and C. L. Zitnick. Structured forests for fast edge detection. In ICCV, 2013.
12. M. Everingham, L. J. V. Gool, C. K. I. Williams, J. M. Winn, and A. Zisserman. The pascal visual object classes (VOC) challenge. IJCV, 88 (2), 2010.
13. A. Faktor and M. Irani. Video segmentation by non-local consensus voting. In BMVC, 2014.
14. Q. Fan, F. Zhong, D. Lischinski, D. Cohen-Or, and B. Chen. Jumpcut: Non-successive mask transfer and interpolation for video cutout. ACM Trans. Graph., 34 (6), 2015.
15. A. Fathi, X. Ren, and J. M. Rehg. Learning to recognize objects in egocentric activities. In CVPR, 2011.
16. R. B. Fisher. The pets04 surveillance ground-truth data sets. 2004.
17. K. Fragkiadaki and J. Shi. Detection free tracking: Exploiting motion and topology for segmenting and tracking under entanglement. In CVPR, 2011.
18. K. Fragkiadaki, G. Zhang, and J. Shi. Video segmentation by tracing discontinuities in a trajectory embedding. In CVPR, 2012.
19. F. Galasso, N. S. Nagaraja, T. J. Cardenas, T. Brox, and B. Schiele. A unified video segmentation benchmark: Annotation, metrics and analysis. In ICCV, 2013.
20. L. Gorelick, M. Blank, E. Shechtman, M. Irani, and R. Basri. Actions as space-time shapes. TPAMI, 29 (12), 2007.
21. M. Grundmann, V. Kwatra, M. Han, and I. A. Essa. Efficient hierarchical graph-based video segmentation. In CVPR, 2010.
22. S. D. Jain and K. Grauman. Supervoxel-consistent foreground propagation in video. In ECCV, 2014.
23. P. Krähenbühl and V. Koltun. Geodesic object proposals. In ECCV, 2014.
24. Y. J. Lee, J. Kim, and K. Grauman. Key-segments for video object segmentation. In Proc. ICCV, 2011.
25. F. Li, T. Kim, A. Humayun, D. Tsai, and J. M. Rehg. Video segmentation by tracking many figure-ground segments. In ICCV, 2013.
26. T. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick. Microsoft COCO: common objects in context. In ECCV, 2014.
27. T. Liu, Z. Yuan, J. Sun, J. Wang, N. Zheng, X. Tang, and H. Shum. Learning to detect a salient object. TPAMI, 33 (2), 2011.
28. D. Martin, C. Fowlkes, and J. Malik. Learning to detect natural image boundaries using local brightness, color, and texture cues. TPAMI, 26 (5), 2004.
29. D. R. Martin, C. Fowlkes, D. Tal, and J. Malik. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In ICCV, 2001.
30. N. Meinshausen and P. Bühlmann. Stability selection. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 72 (4): 417-473, 2010.
31. N. Nicolas Märki, F. Perazzi, O. Wang, and A. Sorkine-Hornung. Bilateral space video segmentation. In CVPR, 2016.
32. S. Oh, A. Hoogs, A. G. A. Perera, and M. Desai. A largescale benchmark dataset for event recognition in surveillance video. In CVPR, 2011.
33. A. Papazoglou and V. Ferrari. Fast object segmentation in unconstrained video. In ICCV, 2013.
34. F. Perazzi, P. Krähenbühl, Y. Pritch, and A. Hornung. Saliency filters: Contrast based filtering for salient region detection. In CVPR, 2012.
35. F. Perazzi, O. Wang, M. Gross, and A. Sorkine-Hornung. Fully connected object proposals for video segmentation. In ICCV, 2015.
36. J. Pont-Tuset, P. Arbeláez, J. T. Barron, F. Marques, and J. Malik. Multiscale combinatorial grouping for image segmentation and object proposal generation. TPAMI, 2016.
37. J. Pont-Tuset and F. Marques. Supervised evaluation of image segmentation and object proposal techniques. TPAMI, 2015.
38. A. Prest, C. Leistner, J. Civera, C. Schmid, and V. Ferrari. Learning object class detectors from weakly annotated video. In CVPR, 2012.
39. L. Rabiner and B.-H. Juang. Fundamentals of speech recognition. 1993.
40. S. A. Ramakanth and R. V. Babu. Seamseg: Video object segmentation using patch seams. In CVPR, 2014.
41. X. Ren and M. Philipose. Egocentric recognition of handled objects: Benchmark and analysis. In CVPR Workshops, 2009.
42. O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. S. Bernstein, A. C. Berg, and F. Li. Imagenet large scale visual recognition challenge. CoRR, abs/1409. 0575, 2014.
43. J. Shen, W. Wenguan, and F. Porikli. Saliency-Aware geodesic video object segmentation. In CVPR, 2015.
44. P. Sundberg, T. Brox, M. Maire, P. Arbelaez, and J. Malik. Occlusion boundary detection and figure/ground assignment from optical flow. In CVPR, 2011.
45. B. Taylor, V. Karasev, and S. Soatto. Causal video object segmentation from persistence of occlusions. In CVPR, 2015.
46. R. Tron and R. Vidal. A benchmark for the comparison of 3-d motion segmentation algorithms. In CVPR, 2007.
47. D. Tsai, M. Flagg, and J. M. Rehg. Motion coherent tracking with multi-label MRF optimization. In BMVC, 2010.
48. S. Vijayanarasimhan and K. Grauman. Active frame selection for label propagation in videos. In ECCV, 2012.
49. T. Wang, B. Han, and J. P. Collomosse. Touchcut: Fast image and video segmentation using single-touch interaction. Computer Vision and Image Understanding, 120, 2014.
50. Y. Wu, J. Lim, and M. Yang. Online object tracking: A benchmark. In CVPR, 2013.
51. C. Xu and J. J. Corso. Evaluation of super-voxel methods for early video processing. In CVPR, 2012.
52. D. Zhang, O. Javed, and M. Shah. Video object segmentation through spatially accurate and temporally dense extraction of primary object regions. In CVPR, 2013.
53. F. Zhong, X. Qin, Q. Peng, and X. Meng. Discontinuityaware video object cutout. ACM Trans. Graph., 31 (6), 2012.