Descriptor learning for omnidirectional image matching

Studies in Computational Intelligence

Volumn 532, Issue , 2014, Pages 49-62

  Masci, Jonathan ^a   Migliore, Davide ^b   Bronstein, Michael M ^c   Schmidhuber, Jürgen ^a  

^a DALLE MOLLE INSTITUTE FOR ARTIFICIAL INTELLIGENCE IDSIA   (Switzerland)

^b Superchrom Srl   (Italy)

^c UNIVERSITY OF LUGANO   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84958552329     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-44907-9_3     Document Type: Article

References (42)

1. Athitsos, V., Alon, J., Sclaroff, S., Kollios, G.: Boostmap: A method for efficient approximate similarity ranking. In: Proc. CVPR (2004
2. Bay, H., Ess, A., Tuytelaars, T., Gool, L.V.: SURF: Speeded Up Robust Features. Computer Vision and Image Understanding 10(3), 346-359 (2008
3. Bogdanova, I., Bresson, X., Thiran, J.P., Vandergheynst, P.: Scale space analysis and active contours for omnidirectional images. Trans. Image Processing 16(7), 1888-1901 (2007), doi:10.1109/TIP.2007.899008
4. Bonarini, A., Burgard, W., Fontana, G., Matteucci, M., Sorrenti, D.G., Tardos, J.D.: Rawseeds: Robotics advancement through web-publishing of sensorial and elaborated extensive data sets. In: Proc. IROS Workshop on Benchmarks in Robotics Research (2006), http://www.robot.uji.es/EURON/en/iros06.htm
5. Briggs, A., Li, Y., Scharstein, D., Wilder, M.: Robot navigation using 1d panoramic images. In: Proc. ICRA (2006
6. Bronstein, A., Bronstein, M., Ovsjanikov, M., Guibas, L.: Shape Google: Geometric words and expressions for invariant shape retrieval. ACM TOG (2010
7. Bronstein, A.M., Bronstein, M.M., Kimmel, R.: Video genome. Tech. Rep. arXiv:1003.5320v1 (2010
8. Bronstein, M.M., Bronstein, A.M., Michel, F., Paragios, N.: Data fusion through crossmodality metric learning using similarity-sensitive hashing. In: Proc. CVPR (2010
9. Ceriani, S., Fontana, G., Giusti, A., Marzorati, D., Matteucci, M., Migliore, D., Rizzi, D., Sorrenti, D.G., Taddei, P.: Rawseeds ground truth collection systems for indoor self-localization and mapping. Autonomous Robots 27(4), 353-371 (2009), http://www.springerlink.com/content/k924032g72818h53/, doi:10.1007/s10514-009-9156-5
10. Cruz, J., Bogdanova, I., Paquier, B., Bierlaire, M., Thiran, J.P.: Scale invariant feature transform on the sphere: Theory and applications. Tech. rep. (2009), http://transp-or2.epfl.ch/technicalReports/ CruzBogdPaquBierThir09.pdf
11. Freund, Y., Schapire, R.: A decision-theoretic generalization of on-line learning and an application to boosting. In: European Conference on Computational Learning Theory, pp. 23-37 (1995
12. Geyer, C., Stewenius, H.: A nine-point algorithm for estimating para-catadioptric fundamental matrices. In: Proc. CVPR (2007
13. Gionis, A., Indik, P., Motwani, R.: Similarity Search in High Dimensions via Hashing. In: International Conference on Very Large Databases (2004
14. Hadsell, R., Chopra, S., LeCun, Y.: Dimensionality reduction by learning an invariant mapping. In: Proc. CVPR (2006
15. Hansen, P.I., Corke, P., Boles, W.: Wide-angle visual feature matching for outdoor localization. Int. J. Robotics Research 29(2/3), 267-297 (2010), http://eprints.qut.edu.au/33736/
16. Jain, P., Kulis, B., Grauman, K.: Fast image search for learned metrics. In: CVPR (2008
17. Jegou, H., Douze, M., Schmid, C.: Hamming embedding and weak geometric consistency for large scale image search. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part I. LNCS, vol. 5302, pp. 304-317. Springer, Heidelberg (2008
18. J'egou, H., Douze, M., Schmid, C.: Packing Bag-of-Features. In: Proc. ICCV (2009
19. J'egou, H., Douze, M., Schmid, C.: Product quantization for nearest neighbor search. Trans. PAMI (2010
20. Kimmel, R., Zhang, C., Bronstein, A.M., Bronstein, M.M.: Are mser features really interesting? Trans. PAMI 32(11), 2316-2320 (2011
21. Kulis, B., Darrell, T.: Learning to hash with binary reconstructive embeddings. In: Proc. NIPS, pp. 1042-1050 (2009
22. Lowe, D.: Distinctive Image Features from Scale-Invariant Keypoints. IJCV 20(2), 91- 110 (2004
23. Mauthner, T., Fraundorfer, F., Bischof, H.: Region matching for omnidirectional images using virtual camera planes. Technology (2006
24. Mei, C., Rives, P.: Single view point omnidirectional camera calibration from planar grids. In: Proc. ICRA (2007
25. Micusik, B., Pajdla, T.: Structure from motion with wide circular field of view cameras. Trans. PAMI 28(7), 1135-1149 (2006), doi:10.1109/TPAMI.2006.151
26. Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., Van Gool, L.: A comparison of affine region detectors. IJCV 65(1/2), 43-72 (2005
27. Nayar, S.K.: Catadioptric Omnidirectional Camera. In: Proc. CVPR (1997
28. Puig, L., Guerrero, J.J.: Scale space for central catadioptric systems. towards a generic camera feature extractor. In: Proc. ICCV (2011
29. Raginsky, M., Lazebnik, S.: Locality-Sensitive Binary Codes from Shift-Invariant Kernels. In: Proc. NIPS (2009
30. Salakhutdinov, R., Hinton, G.: Semantic hashing. In: SIGIR Workshop on Information Retrieval and applications of Graphical Models (2007
31. Scaramuzza, D., Siegwart, R., Martinelli, A.: A robust descriptor for tracking vertical lines in omnidirectional images and its use in mobile robotics. Int. J. Robotics Research 28(2), 149-171 (2009), http://ijr.sagepub. com/cgi/doi/10.1177/0278364908099858
32. Schmidhuber, J., Prelinger, D.: Discovering predictable classifications. Neural Computation 5(4), 625-635 (1993
33. Shakhnarovich, G.: Learning Task-Specific Similarity. Ph.D. thesis, MIT (2005
34. Strecha, C., Bronstein, A.M., Bronstein, M.M., Fua, P.: LDAHash: Improved matching with smaller descriptors. Trans. PAMI (2011
35. Svoboda, T., Pajdla, T.: Matching in catadioptric images with appropriate windows, and outliers removal. In: Skarbek, W. (ed.) CAIP 2001. LNCS, vol. 2124, pp. 733-740. Springer, Heidelberg (2001
36. Taylor, G.W., Spiro, I., Bregler, C., Fergus, R.: Learning invariance through imitation. In: Proc. CVPR (2011
37. Tola, E., Lepetit, V., Fua, P.: Daisy: An Efficient Dense Descriptor Applied toWide Baseline Stereo. Trans. PAMI 32(5), 815-830 (2010
38. Torralba, A., Fergus, R., Freeman, W.T.: 80 million tiny images: A large dataset for nonparametric object and scene recognition. Trans. PAMI 30(11), 1958-1970 (2008
39. Vedaldi, A.: An open implementation of the SIFT detector and descriptor. Tech. Rep. 070012, UCLA CSD (2007
40. Wang, J., Kumar, S., Chang, S.F.: Semi-supervised hashing for scalable image retrieval. In: CVPR (2010
41. Wang, J., Kumar, S., Chang, S.F.: Sequential projection learning for hashing with compact codes. In: ICML (2010
42. Weiss, Y., Torralba, A., Fergus, R.: Spectral hashing (2009