People re-identification by spectral classification of silhouettes

Signal Processing

Volumn 90, Issue 8, 2010, Pages 2362-2374

  Truong Cong, D N ^a   Khoudour, L ^a   Achard, C ^b   Meurie, C ^c   Lezoray, O ^d  

^a Laboratoire Électronique Ondes et Signaux pour les Transports   (France)

^b SORBONNE UNIVERSITÉ   (France)

^c UNIVERSITÉ DE TECHNOLOGIE DE BELFORT MONTBÉLIARD   (France)

^d UNIVERSITÉ DE CAEN   (France)

Author keywords

Color invariant; People tracking; Person re identification; Spectral analysis; Support vector machines; Surveillance systems

Indexed keywords

COLOR INVARIANTS; PEOPLE TRACKING; PERSON RE-IDENTIFICATION; SPECTRAL ANALYSIS; SURVEILLANCE SYSTEMS;

COLOR; IMAGE CLASSIFICATION; NETWORK SECURITY; SECURITY SYSTEMS; SPECTRUM ANALYSIS; SPECTRUM ANALYZERS;

SUPPORT VECTOR MACHINES;

EID: 77951205024     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2009.09.005     Document Type: Article

References (31)

1. 〈http://www.celtic-boss.org/〉.
2. H. Ueda, T. Miyatake, S. Yoshizawa, An interavtive natural motion picture dedicated multimedia authoring system, in: CHI '91 Conference Proceedings, ACM Press, New York, 1991, pp. 343-350.
3. A. Ferman, A. Tekalp, Multiscale content extraction and representation for video indexing, in: Multimedia Storage and Archiving Systems II, Proceedings of the SPIE, vol. 3229, 1997, pp. 23-31.
4. X. Sun, M. Kankanhalli, Y. Zhu, J. Wu, Content-based representative frame extraction for digital video, in: IEEE Conference of Multimedia Computing and Systems, 1998, pp. 190-193.
5. Girgensohn A., and Boreczky J. Time-constrained keyframe selection technique. Multimedia Tools and Applications 11 3 (2000) 347-358
6. Yu Y., Harwood D., Yoon K., and Davis L. Human appearance modeling for matching across video sequences. Machine Vision and Applications 18 3 (2007) 139-149
7. A. Ferman, S. Krishnamachari, A. Tekalp, M. Abdel-Mottaleb, R. Mehrotra, Group-of-frames/pictures color histogram descriptors for multimedia applications, in: Proceedings of the IEEE International Conference on Image Processing, 2000, pp. 65-68.
8. Ferman A., Tekalp A., and Mehrotra R. Robust color histogram descriptors for video segment retrieval and identification. IEEE Transactions on Image Processing 11 5 (2002) 497-508
9. T. Leclercq, L. Khoudour, L. Macaire, J.-G. Postaire, Compact color video signature by principal component analysis, in: Proceedings of the International Conference on Computer Vision and Graphics, 2004, pp. 814-819.
10. N. Gheissari, T. Sebastian, R. Hartley, Person reidentification using spatiotemporal appearance, in: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, Washington, DC, USA, 2006, pp. 1528-1535.
11. F. Porikli, O. Tuzel, Human body tracking by adaptive background models and mean-shift analysis, in: IEEE International Workshop on Performance Evaluation of Tracking and Surveillance, March 2003.
12. D. Hall, J. Nascimento, P. Ribeiro, E. Andrade, P. Moreno, S. Pesnel, T. List, R. Emonet, R. Fisher, J. Victor, J. Crowley, Comparison of target detection algorithms using adaptive background models, in: IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, 2005, pp. 113-120.
13. O. Javed, Z. Rasheed, K. Shafique, M. Shah, Tracking across multiple cameras with disjoint views, in: Ninth IEEE International Conference on Computer Vision, 2003.
14. Yoon K., Harwood D., and Davis L. Appearance-based person recognition using color/path-length profile. Journal of Visual Communication and Image Representation 17 3 (2006) 605-622
15. S. Birchfield, S. Rangarajan, Spatiograms versus histograms for region-based tracking, in: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), vol. 2, 2005, pp. 1158-1163.
16. Buchsbaum G. A spatial processor model for object color perception. Journal of the Franklin Institute 310 1 (1980) 1-26
17. G.D. Finlayson, B. Schiele, J. Crowley, Comprehensive color image normalization, in: Proceedings of the Fifth European Conference on Computer Vision, 1998, pp. 475-490.
18. Finlayson G., Hordley S., Schaefer G., and Yun Tian G. Illuminant and device invariant colour using histogram equalisation. Pattern Recognition 38 2 (2005) 179-190
19. Bengio Y., Delalleau O., Roux N.L., Paiement J.-F., Vincent P., and Ouimet M. Spectral dimensionality reduction. In: Guyon I., Gunn S., Nikravesh M., and Zadeh L. (Eds). Feature Extraction, Foundations and Applications, Studies in Fuzziness and Soft Computing vol. 207 (2006), Springer, Berlin 519-550
20. Saul L., Weinberger K., Ham J., Sha F., and Lee D. Spectral methods for dimensionality reduction. In: Chapelle O., Schölkopf B., and Zien A. (Eds). Semi-Supervised Learning (2006), MIT Press, Cambridge, MA 279-294
21. Roweis S., and Saul L. Nonlinear dimensionality reduction by locally linear embedding. Science 290 5500 (2000) 2323-2326
22. Tenenbaum J.B., de Silva V., and Langford J.C. A global geometric framework for nonlinear dimensionality reduction. Science 290 5500 (2000) 2319-2323
23. Belkin M., and Niyogi P. Laplacian eigenmaps for dimensionality reduction and data representation. Neural Computation 15 6 (2003) 1373-1396
24. B. Nadler, S. Lafon, R.R. Coifman, I.G. Kevrekidis, Diffusion maps, spectral clustering and eigenfunctions of Fokker-Planck operators, in: Advances in Neural Information Processing Systems, 2005, pp. 955-962.
25. A.Y. Ng, M.I. Jordan, Y. Weiss, On spectral clustering: analysis and an algorithm, in: Advances in Neural Information Processing Systems, MIT Press, Cambridge, MA, 2001, pp. 849-856.
26. von Luxburg U. A tutorial on spectral clustering. Statistics and Computing 17 4 (2007) 395-416
27. U. von Luxburg, O. Bousquet, M. Belkin, Consistency of spectral clustering, Technical Report 134, Max Planck Institute for Biological Cybernetics, 2004.
28. Vapnik V.N. Statistical Learning Theory (1998), Wiley, New York
29. Shawe-Taylor J., and Cristianini N. Support Vector Machines and Other Kernel-based Learning Methods (2000), Cambridge University Press, Cambridge, MA
30. J. Platt, Fast training of support vector machines using sequential minimal optimization, in: Advances in Kernel Methods-Support Vector Learning, MIT Press, Cambridge, MA, 1999, pp. 185-208.
31. C.-C. Chang, C.-J. Lin, LIBSVM: a library for support vector machines, Software Available at: 〈http://www.csie.ntu.edu.tw/∼cjlin/libsvm〉, 2001.