Video object retrieval by trajectory and appearance

IEEE Transactions on Circuits and Systems for Video Technology

Volumn 25, Issue 6, 2015, Pages 1026-1037

  Lai, Yuan Hao ^a   Yang, Chuan Kai ^a  

^a NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

Author keywords

Object reidentification; Object tracking; Video retrieval.

Indexed keywords

EMBEDDED SYSTEMS; GRAPHICAL USER INTERFACES; INFORMATION RETRIEVAL; MOBILE DEVICES; MOTION ESTIMATION; SECURITY SYSTEMS; USER INTERFACES; VIDEO RECORDING;

INTUITIVE INTERACTION; OBJECT TRACKING; RE IDENTIFICATIONS; SURVEILLANCE SYSTEMS; VIDEO OBJECT RETRIEVAL; VIDEO RETRIEVAL; VIDEO RETRIEVAL SYSTEM; VISUAL INFORMATION;

SEARCH ENGINES;

EID: 84951837691     PISSN: 10518215     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCSVT.2014.2358022     Document Type: Article

References (55)

1. X. Ma, X. Chen, A. Khokar, and D. Schonfeld, "Motion trajectorybased video retrieval, classification, and summarization," Video Search and Mining (Studies in Computational Intelligence), vol. 287. Berlin, Germany: Springer-Verlag, 2010, pp. 53-82.
2. X. Chen, D. Schonfeld, and A. Khokhar, "Robust null space representation and sampling for view-invariant motion trajectory analysis," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2008, pp. 1-6.
3. D. Buzan, S. Sclaroff, and G. Kollios, "Extraction and clustering of motion trajectories in video," in Proc. 17th Int. Conf. Pattern Recognit. (ICPR), Cambridge, U.K., Aug. 2004, pp. 521-524.
4. M. Aly, M. Munich, and P. Perona, "Bag of words for large scale object recognition: Properties and benchmark," in Proc. Int. Conf. Comput. Vis. Theory Appl. (VISAPP), Mar. 2011, pp. 299-306.
5. H. Grabner, P. M. Roth, and H. Bischof, "Is pedestrian detection really a hard task?" in Proc. IEEE Int. Workshop Perform. Eval. Tracking Surveill., Aug. 2007, pp. 1-8.
6. P. M. Roth, H. Grabner, D. Skocaj, H. Bischol, and A. Leonardis, "On-line conservative learning for person detection," in Proc. 2nd Joint IEEE Int. Workshop Vis. Surveill. Perform. Eval. Tracking Surveill., Oct. 2005, pp. 223-230.
7. I. N. Junejo, O. Javed, and M. Shah, "Multi feature path modeling for video surveillance," in Proc. 17th Int. Conf. Pattern Recognit., vol. 2. Aug. 2004, pp. 716-719.
8. C. Li, Z. Han, Q. Ye, and J. Jiao, "Abnormal behavior detection via sparse reconstruction analysis of trajectory," in Proc. 6th Int. Conf. Image Graph., Aug. 2011, pp. 807-810.
9. M. Bastan, H. Cam, U. Gudukbay, and O. Ulusoy, "BilVideo-7: An MPEG-7 compatible video indexing and retrieval system," IEEE Multi-Media, vol. 17, no. 3, pp. 62-73, Jul. 2010.
10. D. DeMenthon and D. Doermann, "Video retrieval using spatio-temporal descriptors," in Proc. 11th ACM Int. Conf. Multimedia, New York, NY, USA, 2003, pp. 508-517.
11. S.-F. Chang, W. Chen, H. J. Meng, H. Sundaram, and D. Zhong, "A fully automated content-based video search engine supporting spatiotemporal queries," IEEE Trans. Circuits Syst. Video Technol., vol. 8, no. 5, pp. 602-615, Sep. 1998.
12. F. de la Torre Frade, E. M. Marroquin, M. E. S. Pérez, and J. A. M. Moreno, "Moving object detection and tracking system: A real-time implementation," in Proc. Groupe dEtudes du Traitement du Signal et des Images (GRETSI), 1997, pp. 375-378.
13. A. Yilmaz, "Object tracking by asymmetric kernel mean shift with automatic scale and orientation selection," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2007, pp. 1-6.
14. Y. Wei, J. Sun, X. Tang, and H.-Y. Shum, "Interactive offline tracking for color objects," in Proc. IEEE 11th Int. Conf. Comput. Vis. (ICCV), Oct. 2007, pp. 1-8.
15. Z. Kalal, J. Matas, and K. Mikolajczyk, "Online learning of robust object detectors during unstable tracking," in Proc. IEEE 12th Int. Conf. Comput. Vis. Workshops (ICCV Workshops), Sep./Oct. 2009, pp. 1417-1424.
16. C. Stauffer and W. E. L. Grimson, "Learning patterns of activity using real-time tracking," IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 8, pp. 747-757, Aug. 2000.
17. W. Chen and S.-F. Chang, "Motion trajectory matching of video objects," Proc. SPIE, vol. 3972, pp. 544-553, Jan. 2000.
18. J. B. Zheng, D. D. Feng, and R.-C. Zhao, "Trajectory matching and classification of video moving objects," in Proc. IEEE 7th Workshop Multimedia Signal Process., Oct./Nov. 2005, pp. 1-4.
19. F. I. Bashir, A. A. Khokhar, and D. Schonfeld, "View-invariant motion trajectory-based activity classification and recognition," Multimedia Syst., vol. 12, no. 1, pp. 45-54, Aug. 2006.
20. F. I. Bashir, A. A. Khokhar, and D. Schonfeld, "Real-time motion trajectory-based indexing and retrieval of video sequences," IEEE Trans. Multimedia, vol. 9, no. 1, pp. 58-65, Jan. 2007.
21. J. Yang, Y. F. Li, K. Wang, Y. Wu, G. Altieri, and M. Scalia, "Mixed signature descriptor with global invariants for 3D motion trajectory perception and recognition," Math. Problems Eng., vol. 2012, Jan. 2012, Art. ID 613939.
22. H.-T. Pham, J.-J. Kim, and Y. Won, "A cost effective method for matching the 3D motion trajectories," IT Convergence and Security (Lecture Notes in Electrical Engineering), vol. 215. New York, NY, USA: Springer-Verlag, 2013, pp. 889-895.
23. F. Dornaika and F. Chakik, "Efficient object detection and matching using feature classification," in Proc. 20th Int. Conf. Pattern Recognit. (ICPR), Aug. 2010, pp. 3073-3076.
24. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Comput. Vis., vol. 60, no. 2, pp. 91-110, 2004.
25. H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool, "SURF: Speeded up robust features," Comput. Vis. Image Understand., vol. 110, no. 3, pp. 346-359, 2008.
26. A. Alahi, D. Marimon, M. Bierlaire, and M. Kunt, "A master-slave approach for object detection and matching with fixed and mobile cameras," in Proc. 15th IEEE Int. Conf. Image Process., Oct. 2008, pp. 1712-1715.
27. M. Bassiouny and M. El-Saban, "Object matching using feature aggregation over a frame sequence," in Proc. IEEE Workshop Appl. Comput. Vis. (WACV), Jan. 2011, pp. 95-102.
28. J. Sivic and A. Zisserman, "Efficient visual search of videos cast as text retrieval," IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 4, pp. 591-606, Apr. 2009. [Online]. Available: http://dx.doi.org/10.1109/TPAMI.2008.111
29. H. Kang, A. A. Efros, M. Hebert, and T. Kanade, "Image matching in large scale indoor environment," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. Workshop Egocentric Vis. (CVPR), Jun. 2009, pp. 33-40.
30. L. F. Teixeira and L. Corte-Real, "Video object matching across multiple independent views using local descriptors and adaptive learning," Pattern Recognit. Lett., vol. 30, no. 2, pp. 157-167, Jan. 2009.
31. N. A. Bhatti and A. Hanbury, "Co-occurrence bag of words for object recognition," in Proc. 15th Comput. Vis. Winter Worshop, Feb. 2010, pp. 21-28.
32. J. van de Weijer and F. S. Khan, "Fusing color and shape for bagof-words based object recognition," in Computational Color Imaging. Berlin, Germany: Springer-Verlag, 2013, pp. 25-34.
33. R. S. Hunter, "Photoelectric color difference meter," J. Opt. Soc. Amer., vol. 48, no. 12, pp. 985-993, 1958.
34. V. Pham, P. Vo, V. T. Hung, and L. H. Bac, "GPU implementation of extended Gaussian mixture model for background subtraction," in Proc. IEEE Int. Conf. Comput. Commun. Technol., Res., Innov., Vis. Future (RIVF), Nov. 2010, pp. 1-4.
35. B. D. Lucas and T. Kanade, "An iterative image registration technique with an application to stereo vision (DARPA)," in Proc. DARPA Image Understand. Workshop, Apr. 1981, pp. 121-130.
36. H. M. Dee and D. C. Hogg, "On the feasibility of using a cognitive model to filter surveillance data," in Proc. IEEE Conf. Adv. Video Signal Based Surveill. (AVSS), Sep. 2005, pp. 34-39.
37. Y. Freund and R. E. Schapire, "A decision-theoretic generalization of on-line learning and an application to boosting," in Proc. 2nd Eur. Conf. Comput. Learn. Theory (EuroCOLT), 1995, pp. 23-37.
38. N. Friedman and S. Russell, "Image segmentation in video sequences: A probabilistic approach," in Proc. 13th Conf. Uncertainty Artif. Intell. (UAI), 1997, pp. 175-181.
39. Z. Zivkovic, "Improved adaptive Gaussian mixture model for background subtraction," in Proc. 17th Int. Conf. Pattern Recognit. (ICPR), vol. 2. Aug. 2004, pp. 28-31.
40. J. C. S. Jacques, C. R. Jung, and S. Raupp Musse, "Background subtraction and shadow detection in grayscale video sequences," in Proc. 18th Brazilian Symp. Comput. Graph. Image Process. (SIBGRAPI), Oct. 2005, pp. 189-196.
41. A. Sanin, C. Sanderson, and B. C. Lovell, "Improved shadow removal for robust person tracking in surveillance scenarios," in Proc. 20th Int. Conf. Pattern Recognit. (ICPR), Aug. 2010, pp. 141-144.
42. R. R. Sillito and R. B. Fisher, "Semi-supervised learning for anomalous trajectory detection," in Proc. BMVC, 2008, pp. 1-10.
43. J.-W. Hsieh, S.-L. Yu, and Y.-S. Chen, "Motion-based video retrieval by trajectory matching," IEEE Trans. Circuits Syst. Video Technol., vol. 16, no. 3, pp. 396-409, Mar. 2006.
44. S. Jeannin and A. Divakaran, "MPEG-7 visual motion descriptors," IEEE Trans. Circuits Syst. Video Technol., vol. 11, no. 6, pp. 720-724, Jun. 2001.
45. T. Gotoh, T. Miyoshi, Y. Takaya, and T. Edamitsu, "B-spline curve fitting onto measured point data under consideration of curvature," J. Int. Soc. Precis. Eng. Nanotechnol., vol. 60, no. 7, pp. 964-968, 1994.
46. H. Freeman, "On the encoding of arbitrary geometric configurations," IRE Trans. Electron. Comput., vol. EC-10, no. 2, pp. 260-268, Jun. 1961.
47. G. Salton and C. Buckley, "Term-weighting approaches in automatic text retrieval," Inf. Process. Manage., vol. 24, no. 5, pp. 513-523, 1988.
48. CAVIAR: Context Aware Vision Using Image-Based Active Recognition. [Online]. Available: http://homepages.inf.ed.ac.uk/rbf/CAVIAR/, accessed Jul. 1, 2012.
49. BEHAVE: Computer-Assisted Prescreening of Video Streams for Unusual Activities. [Online]. Available: http://groups.inf.ed.ac.uk/vision/BEHAVEDATA/INTERACTIONS/, accessed Jul. 1, 2012.
50. T. Yu, Y. Wu, N. O. Krahnstoever, and P. H. Tu, "Distributed data association and filtering for multiple target tracking," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2008, pp. 1-8.
51. S. Agarwal, A. Awan, and D. Roth, "Learning to detect objects in images via a sparse, part-based representation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 11, pp. 1475-1490, Nov. 2004.
52. S. Bak, E. Corvee, F. Bremond, and M. Thonnat, "Person reidentification using Haar-based and DCD-based signature," in Proc. 7th IEEE Int. Conf. Adv. Video Signal Based Surveill. (AVSS), Aug./Sep. 2010, pp. 1-8.
53. L. Bazzani, M. Cristani, A. Perina, and V. Murino, "Multiple-shot person re-identification by chromatic and epitomic analyses," Pattern Recognit. Lett., vol. 33, no. 7, pp. 898-903, May 2012.
54. D. S. Cheng, M. Cristani, M. Stoppa, L. Bazzani, and V. Murino, "Custom pictorial structures for re-identification," in Proc. Brit. Mach. Vis. Conf., 2011, pp. 68.1-68.11.
55. O. Hamdoun, F. Moutarde, B. Stanciulescu, and B. Steux, "Person reidentification in multi-camera system by signature based on interest point descriptors collected on short video sequences," in Proc. 2nd ACM/IEEE Int. Conf. Distrib. Smart Cameras, Sep. 2008, pp. 1-6.