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Abstract
In this paper we address the problem of re-identification of people: given a camera network with non-overlapping fields of view, we study the problem of how to correctly pair detections in different cameras (one to many problem, search for similar cases) or match detections to a database of individuals (one to one, search for best match case). We propose a novel color histogram based features which increases the re-identification rate. Furthermore we evaluate five different classifiers: three fixed distance metrics, one learned distance metric and a classifier based on sparse representation, novel to the field of re-identification. A new database alongside with the matlab code produced are made available on request.
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Bay, H., Tuytelaars, T., Gool, L.V.: Surf: Speeded up robust features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)
Boult, T.E., Micheals, R.J., Gao, X., Eckmann, M.: Into the woods: Visual surveillance of noncooperative and camouflaged targets in complex outdoor settings. Proceedings of The IEEE 89, 1382–1402 (2001)
Comaniciu, D., Ramesh, V., Meer, P.: Real-time tracking of non-rigid objects using mean shift. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2000, vol. 2, pp. 142 –149 (2000)
Donoho, D.L.: For most large underdetermined systems of linear equations the minimal l1-norm solution is also the sparsest solution. Comm. Pure Appl. Math. 59, 797–829 (2004)
Hamdoun, O., Moutarde, F., Stanciulescu, B., Steux, B.: Person re-identification in multi-camera system by signature based on interest point descriptors collected on short video sequences, pp. 1 –6 (September 2008)
Javed, O., Rasheed, Z., Shafique, K., Shah, M.: Tracking across multiple cameras with disjoint views. In: Proceedings of Ninth IEEE International Conference on Computer Vision, 2003, vol. 2, pp. 952–957 (2003)
Ling, H., Okada, K.: Diffusion distance for histogram comparison. In: CVPR 2006: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 246–253. IEEE Computer Society, Washington, DC, USA (2006)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints (2003)
Teixeira, L.F., Corte-Real, L.: Video object matching across multiple independent views using local descriptors and adaptive learning. Pattern Recognition Letters 30(2), 157 (2009); video-based Object and Event Analysis
Truong Cong, D.N., Achard, C., Khoudour, L., Douadi, L.: Video sequences association for people re-identification across multiple non-overlapping cameras. In: Foggia, P., Sansone, C., Vento, M. (eds.) ICIAP 2009. LNCS, vol. 5716, pp. 179–189. Springer, Heidelberg (2009)
Wright, J., Yang, A., Ganesh, A., Sastry, S., Ma, Y.: Robust face recognition via sparse representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(2), 210–227 (2009)
Xing, E.P., Ng, A.Y., Jordan, M.I., Russell, S.: Distance metric learning, with application to clustering with side-information. In: Advances in Neural Information Processing Systems, vol. 15, pp. 505–512. MIT Press, Cambridge (2002)
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Authors and Affiliations
Institute for Systems and Robotics, Instituto Superior Técnico, 1049-001, Lisboa, Portugal
Dario Figueira & Alexandre Bernardino
- Dario Figueira
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- Alexandre Bernardino
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Editors and Affiliations
Department of Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Waterloo, ON, Canada
Mohamed Kamel
Faculty of Engineering, Institute of Biomedical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal
Aurélio Campilho
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Figueira, D., Bernardino, A. (2011). Re-identification of Visual Targets in Camera Networks: A Comparison of Techniques. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21593-3_30
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