Online Deformable Object Tracking Based on Structure-Aware Hyper-Graph

IEEE Transactions on Image Processing

Volumn 25, Issue 8, 2016, Pages 3572-3584

  Du, Dawei ^a   Qi, Honggang ^a   Li, Wenbo ^b   Wen, Longyin ^c   Huang, Qingming ^a,d   Lyu, Siwei ^c  

^a UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^b Lehigh University   (United States)

^c State University of New York   (United States)

^d INSTITUTE OF COMPUTING TECHNOLOGY   (China)

Author keywords

deformable object tracking; dense subgraph searching; Online tracking; part based model; structure aware hyper graph

Indexed keywords

DEFORMATION; TRACKING (POSITION);

DEFORMABLE OBJECT; DENSE SUBGRAPH; HYPER GRAPH; ON-LINE TRACKING; PART-BASED MODELS;

TARGET TRACKING;

EID: 84977506318     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2016.2570556     Document Type: Article

References (51)

1. R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Süsstrunk, "SLIC superpixels compared to state-of-the-art superpixel methods," IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 11, pp. 2274-2282, Nov. 2012.
2. A. Adam, E. Rivlin, and I. Shimshoni, "Robust fragments-based tracking using the integral histogram," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2006, pp. 798-805.
3. O. Arandjelovíc, "Contextually learnt detection of unusual motion-based behaviour in crowded public spaces," in Proc. Int. Symp. Comput. Inf. Sci., 2011, pp. 403-410.
4. B. Babenko, M.-H. Yang, and S. Belongie, "Robust object tracking with online multiple instance learning," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 8, pp. 1619-1632, Aug. 2011.
5. Y. Boykov and V. Kolmogorov, "An experimental comparison of mincut/max-flow algorithms for energy minimization in vision," IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 9, pp. 1124-1137, Sep. 2004.
6. G. J. Brostow and R. Cipolla, "Unsupervised Bayesian detection of independent motion in crowds," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2006, pp. 594-601.
7. T. Brox and J. Malik, "Large displacement optical flow: Descriptor matching in variational motion estimation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 3, pp. 500-513, Mar. 2011.
8. Z. Cai, L.Wen, Z. Lei, N. Vasconcelos, and S. Z. Li, "Robust deformable and occluded object tracking with dynamic graph," IEEE Trans. Image Process., vol. 23, no. 12, pp. 5497-5509, Dec. 2014.
9. L. Cehovin, M. Kristan, and A. Leonardis, "Robust visual tracking using an adaptive coupled-layer visual model," IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 4, pp. 941-953, Apr. 2013.
10. J. Chang and J. W. Fisher, III, "Topology-constrained layered tracking with latent flow," in Proc. IEEE Int. Conf. Comput. Vis., Dec. 2013, pp. 161-168.
11. M. Danelljan, F. S. Khan, M. Felsberg, and J. Van de Weijer, "Adaptive color attributes for real-time visual tracking," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jan. 2014, pp. 1090-1097.
12. T. B. Dinh, N. Vo, and G. Medioni, "Context tracker: Exploring supporters and distracters in unconstrained environments," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2011, pp. 1177-1184.
13. S. Duffner and C. Garcia, "PixelTrack: A fast adaptive algorithm for tracking non-rigid objects," in Proc. IEEE Int. Conf. Comput. Vis., Dec. 2013, pp. 2480-2487.
14. M. Felsberg et al., "The thermal infrared visual object tracking VOT-TIR2015 challenge results," in Proc. Workshops Conjunct Int. Conf. Comput. Vis., Dec. 2015, pp. 639-651.
15. M. Godec, P. M. Roth, and H. Bischof, "Hough-based tracking of non-rigid objects," in Proc. IEEE Int. Conf. Comput. Vis., Nov. 2011, pp. 81-88.
16. H. Grabner, J. Matas, L. Van Gool, and P. Cattin, "Tracking the invisible: Learning where the object might be," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2010, pp. 1285-1292.
17. M. Grundmann, V. Kwatra, M. Han, and I. Essa, "Efficient hierarchical graph-based video segmentation," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2010, pp. 2141-2148.
18. S. Hare, A. Saffari, and P. H. S. Torr, "Struck: Structured output tracking with kernels," in Proc. IEEE Int. Conf. Comput. Vis., Nov. 2011, pp. 263-270.
19. Z. Hong, C. Wang, X. Mei, D. Prokhorov, and D. Tao, "Tracking using multilevel quantizations," in Proc. Eur. Conf. Comput. Vis., vol. 8694. 2014, pp. 155-171.
20. X. Jia, H. Lu, and M.-H. Yang, "Visual tracking via adaptive structural local sparse appearance model," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2012, pp. 1822-1829.
21. Z. Kalal, J. Matas, and K. Mikolajczyk, "P-N learning: Bootstrapping binary classifiers by structural constraints," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2010, pp. 49-56.
22. D. A. Klein and A. B. Cremers, "Boosting scalable gradient features for adaptive real-time tracking," in Proc. IEEE Int. Conf. Robot. Autom., May 2011, pp. 4411-4416.
23. J. Kwon and K. M. Lee, "Tracking of a non-rigid object via patchbased dynamic appearance modeling and adaptive basin hopping Monte Carlo sampling," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2009, pp. 1208-1215.
24. A. Li, M. Li, Y. Wu, M.-H. Yang, and S. Yan, "NUS-PRO: A new visual tracking challenge," IEEE Trans. Pattern Anal. Mach. Intell., vol. 38, no. 2, pp. 335-349, Feb. 2016.
25. W. Li, L. Wen, M. C. Chuah, Y. Zhang, Z. Lei, and S. Z. Li, "Online visual tracking using temporally coherent part cluster," in Proc. IEEE Winter Conf. Appl. Comput. Vis., Jan. 2015, pp. 9-16.
26. J. Lim, D. A. Ross, R.-S. Lin, and M.-H. Yang, "Incremental learning for visual tracking," in Proc. Adv. Neural Inf. Process. Syst., 2004, pp. 793-800.
27. H. Liu, L. J. Latecki, and S. Yan, "Robust clustering as ensembles of affinity relations," in Proc. Adv. Neural Inf. Process. Syst., 2010, pp. 1414-1422.
28. R. Martin and O. Arandjelovíc, "Multiple-object tracking in cluttered and crowded public spaces," in Proc. Int. Symp. Vis. Comput., 2010, pp. 89-98.
29. X. Mei and H. Ling, "Robust visual tracking using 1 minimization," in Proc. IEEE Int. Conf. Comput. Vis., Sep./Oct. 2009, pp. 1436-1443.
30. S. M. S. Nejhum, J. Ho, and M.-H. Yang, "Online visual tracking with histograms and articulating blocks," Comput. Vis. Image Understand., vol. 114, no. 8, pp. 901-914, Aug. 2010.
31. S. Oron, A. Bar-Hillel, D. Levi, and S. Avidan, "Locally orderless tracking," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2012, pp. 1940-1947.
32. Y. Qi et al., "Hedged deep tracking," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2016, to be published.
33. X. Ren and J. Malik, "Tracking as repeated figure/ground segmentation," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2007, pp. 1-8.
34. J. Santner, C. Leistner, A. Saffari, T. Pock, and H. Bischof, "PROST: Parallel robust online simple tracking," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2010, pp. 723-730.
35. S. Shalev-Shwartz, Y. Singer, N. Srebro, and A. Cotter, "Pegasos: Primal estimated sub-gradient solver for SVM," Math. Program., vol. 127, no. 1, pp. 3-30, Mar. 2011.
36. S. Song and J. Xiao, "Tracking revisited using RGBD camera: Unified benchmark and baselines," in Proc. IEEE Int. Conf. Comput. Vis., Dec. 2013, pp. 233-240.
37. M. Kristan et al., "The visual object tracking VOT2014 challenge results," in Proc. Workshops Conjunct Eur. Conf. Comput. Vis., 2014, pp. 191-217.
38. S. Wang, H. Lu, F. Yang, and M.-H. Yang, "Superpixel tracking," in Proc. IEEE Int. Conf. Comput. Vis., Nov. 2011, pp. 1323-1330.
39. L. Wen, Z. Cai, D. Du, Z. Lei, and S. Z. Li, "Learning discriminative hidden structural parts for visual tracking," in Proc. Workshops Conjunct Asian Conf. Comput. Vis., 2014, pp. 262-276.
40. L. Wen, Z. Cai, Z. Lei, D. Yi, and S. Z. Li, "Online spatio-temporal structural context learning for visual tracking," in Proc. Eur. Conf. Comput. Vis., 2012, pp. 716-729.
41. L. Wen, Z. Cai, Z. Lei, D. Yi, and S. Z. Li, "Robust online learned spatio-temporal context model for visual tracking," IEEE Trans. Image Process., vol. 23, no. 2, pp. 785-796, Feb. 2014.
42. L. Wen, Z. Cai, M. Yang, Z. Lei, D. Yi, and S. Z. Li, "Online multiple instance joint model for visual tracking," in Proc. IEEE Int. Conf. Adv. Video Signal-Based Surveill., Sep. 2012, pp. 319-324.
43. L. Wen, D. Du, Z. Lei, S. Z. Li, and M.-H. Yang, "JOTS: Joint online tracking and segmentation," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2015, pp. 2226-2234.
44. L. Wen, W. Li, J. Yan, Z. Lei, D. Yi, and S. Z. Li, "Multiple target tracking based on undirected hierarchical relation hypergraph," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2014, pp. 1282-1289.
45. Y. Wu, J. Lim, and M.-H. Yang, "Online object tracking: A benchmark," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2013, pp. 2411-2418.
46. M. Yang, Y. Wu, and G. Hua, "Context-aware visual tracking," IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 7, pp. 1195-1209, Jul. 2009.
47. R. Yao, Q. Shi, C. Shen, Y. Zhang, and A. Van Den Hengel, "Part-based visual tracking with online latent structural learning," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2013, pp. 2363-2370.
48. K. Zhang, L. Zhang, Q. Liu, D. Zhang, and M.-H. Yang, "Fast visual tracking via dense spatio-temporal context learning," in Proc. Eur. Conf. Comput. Vis., 2014, pp. 127-141.
49. K. Zhang, L. Zhang, and M.-H. Yang, "Real-time compressive tracking," in Proc. Eur. Conf. Comput. Vis., 2012, pp. 864-877.
50. T. Zhang, B. Ghanem, S. Liu, and N. Ahuja, "Robust visual tracking via multi-task sparse learning," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2012, pp. 2042-2049.
51. W. Zhong, H. Lu, and M.-H. Yang, "Robust object tracking via sparsitybased collaborative model," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2012, pp. 1838-1845.