Abstract
Vehicle identification from images has been predominantly addressed through automatic license plate recognition (ALPR) techniques which detect and recognize the characters in the plate region of the image. We move away from traditional ALPR techniques and advocate for a data-driven approach for vehicle identification. Here, given a plate image region, the idea is to search for a near-duplicate image in an annotated database; if found, the identity of the near-duplicate is transferred to the input region. Although this approach could be perceived as impractical, we actually demonstrate that it is feasible with state-of-the-art image representations, and that it presents some advantages in terms of speed, and time-to-deploy. To overcome the issue of identifying previously unseen identities, we propose an image simulation approach where photo-realistic images of license plates are generated for desired plate numbers. We demonstrate that there is no perceivable performance difference between using synthetic and real plates. We also improve the matching accuracy using similarity learning, which is in the spirit of domain adaptation.
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References
Arth, C., Limberger, F., Bischof, H.: Real-time license plate recognition on an embedded DSP-platform. In: CVPR (2007)
Donoser, M., Arth, C., Bischof, H.: Detecting, Tracking and Recognizing License Plates. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds.) ACCV 2007, Part II. LNCS, vol. 4844, pp. 447–456. Springer, Heidelberg (2007)
Anagnostopoulos, C.N.E., Anagnostopoulos, I.E., Psoroulas, I.D., Loumos, V., Kayafas, E.: License plate recognition from still images and video sequences: A survey. IEEE Trans. on Intelligent Transportation Systems 9 (2008)
Chang, S.L., Chen, L.S., Chung, Y.C., Chen, S.W.: Automatic license plate recognition. IEEE Trans. on Intelligent Transportation Systems 5, 42–53 (2004)
Perronnin, F., Sánchez, J., Mensink, T.: Improving the Fisher Kernel for Large-Scale Image Classification. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part IV. LNCS, vol. 6314, pp. 143–156. Springer, Heidelberg (2010)
Chatfield, K., Lempitsky, V., Vedaldi, A., Zisserman, A.: The devil is in the details: an evaluation of recent feature encoding methods. In: BMVC (2011)
Bala, R., Zhao, Y., Burry, A., Kozitsky, V., Fillion, C., Saunders, C., Rodriguez-Serrano, J.A.: Image simulation for automatic license plate recognition. In: Proceedings of SPIE, vol. 8305 (2012)
Kulis, B., Saenko, K., Darrell, T.: What you saw is not what you get: Domain adaptation using asymmetric kernel transforms. In: CVPR (2011)
Jégou, H., Perronnin, F., Douze, M., Sánchez, J., Pérez, P., Schmid, C.: Aggregating local image descriptors into compact codes. IEEE Trans. on PAMI (2011)
Hays, J., Efros, A.A.: im2gps: estimating geographic information from a single image. In: CVPR (2008)
Hays, J., Efros, A.A.: Scene completion using millions of photographs. ACM Trans. on Graphics 26 (2007)
Marin, J., Vazquez, D., Gerenimo, D., Lopez, A.M.: Learning appearance in virtual scenarios for pedestrian detection. In: CVPR (2010)
Schels, J., Liebelt, J., Schertler, K., Lienhart, R.: Synthetically trained multi-view object class and viewpoint detection for advanced image retrieval. In: ICMR (2011)
Wang, K., Babenko, B., Belongie, S.: End-to-end scene text recognition. In: ICCV (2011)
Konidaris, T., Gatos, B., Ntzios, K., Pratikakis, I., Theodoridis, S., Perantonis, S.J.: Keyword-guided word spotting in historical printed documents using synthetic data and user feedback. IJDAR 9, 167–177 (2007)
Rodríguez-Serrano, J.A., Perronnin, F.: Synthesizing queries for handwritten word image retrieval. Pattern Recognition 45, 3270–3276 (2012)
Bai, B., Weston, J., Grangier, D., Collobert, R., Chapelle, O., Weinberger, K.: Supervised semantic indexing. In: CIKM (2009)
Weinberger, K., Saul, L.: Distance metric learning for large margin nearest neighbor classification. JMLR (2009)
Bottou, L.: Stochastic Learning. In: Bousquet, O., von Luxburg, U., Rätsch, G. (eds.) Machine Learning 2003. LNCS (LNAI), vol. 3176, pp. 146–168. Springer, Heidelberg (2004)
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Rodriguez-Serrano, J.A., Sandhawalia, H., Bala, R., Perronnin, F., Saunders, C. (2012). Data-Driven Vehicle Identification by Image Matching. In: Fusiello, A., Murino, V., Cucchiara, R. (eds) Computer Vision – ECCV 2012. Workshops and Demonstrations. ECCV 2012. Lecture Notes in Computer Science, vol 7584. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33868-7_53
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DOI: https://doi.org/10.1007/978-3-642-33868-7_53
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