Scale invariant feature transform on the sphere: Theory and applications

International Journal of Computer Vision

Volumn 98, Issue 2, 2012, Pages 217-241

  Cruz Mota, Javier ^a   Bogdanova, Iva ^a   Paquier, Benoît ^a   Bierlaire, Michel ^a   Thiran, Jean Philippe ^a  

^a EPFL   (Switzerland)

Author keywords

(Spherical) image processing; Feature extraction; Matching; Object detection; Omnidirectional vision; SIFT

Indexed keywords

ACCURATE PERFORMANCE; DESCRIPTORS; LOCAL DESCRIPTORS; MATCHING; MATCHING PROCESS; OBJECT DETECTION; OMNI-DIRECTIONAL VISION; OMNIDIRECTIONAL IMAGE; PLANAR IMAGES; POINT-MATCHING; SCALE INVARIANT FEATURE TRANSFORMS; SIFT; SIFT DESCRIPTORS; SPHERICAL COORDINATES;

ALGORITHMS; FEATURE EXTRACTION; IMAGE PROCESSING; SPHERES; TRACKING (POSITION);

IMAGE MATCHING;

EID: 84868303542     PISSN: 09205691     EISSN: 15731405     Source Type: Journal    
DOI: 10.1007/s11263-011-0505-4     Document Type: Article

References (40)

1. Barut, A. O., & Ra̧czka, R. (1986). Theory of group representations and applications (2nd edn.). Singapore: World Scientific. ISBN 9971502178.
2. Baumberg, A. (2000). Reliable feature matching across widely separated views. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 774-781).
3. Bay, H., Ess, A., Tuytelaars, T., & Van Gool, L. (2008). Speeded-up robust features (SURF). Computer Vision and Image Understanding, 110(3), 346-359. http://www.sciencedirect.com/science/article/B6WCX-4RC2S4T-2/1/ cddc9c43940bd8fb62d6ed668de29e20.
4. Bogdanova, I., Bresson, X., Thiran, J. P., & Vandergheynst, P. (2007). Scale-space analysis and active contours for omnidirectional images. IEEE Transactions on Image Processing, 16(7), 1888-1901. (Pubitemid 47018885)
5. Boult, T. E., Micheals, R. J., Gao, X., & Eckmann, M. (2001). Into the woods: visual surveillance of noncooperative and camouflaged targets in complex outdoor settings. Proceedings of the IEEE, 89(10), 1382-1402. doi:10.1109/5.959337.
6. Brox, T., Cremers, D., Gall, J., & Rosenhahn, B. (2010). Combined region- and motion-based 3d tracking of rigid and articulated objects. IEEE Transactions on Pattern Analysis and Machine Intelligence. doi:10.1109/TPAMI. 2009.32.
7. Bulow, T. (2004). Spherical diffusion for 3d surface smoothing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(12), 1650-1654. doi:10.1109/TPAMI.2004.129.
8. Bur, A., Tapus, A., Ouerhani, N., Siegwart, R., & Hugli, H. (2006). Robot navigation by panoramic vision and attention guided features. In Proceedings of the 18th international conference on pattern recognition, Washington DC (pp. 695-698). (Pubitemid 46531997)
9. Chen, C. H., Yao, Y., Page, D., Abidi, B., Koschan, A., & Abidi, M. (2008). Heterogeneous fusion of omnidirectional and PTZ cameras for multiple object tracking. IEEE Transactions on Circuits and Systems for Video Technology, 18(8), 1052-1063. doi:10.1109/TCSVT.2008.928223.
10. Driscoll, J., & Healy, D. (1994). Computing Fourier transforms and convolutions on the 2-sphere. Advances in Applied Mathematics, 15(2), 202-250. doi:10.1006/aama.1994.1008.
11. Ehlgen, T., Pajdla, T., & Ammon, D. (2008). Eliminating blind spots for assisted driving. IEEE Transactions on Intelligent Transportation Systems, 9(4), 657-665. doi:10.1109/TITS.2008.2006815.
12. Fischler, M. A., & Bolles, R. C. (1981). Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM, 24, 381-395.
13. Geyer, C., & Daniilidis, K. (2001). Catadioptric projective geometry. International Journal of Computer Vision, 45(3), 223-243.
14. Goedeme, T., Tuytelaars, T., Van Gool, L., Vanacker, G., & Nuttin, M. (2005). Omnidirectional sparse visual path following with occlusion-robust feature tracking. In Workshop on omnidirectional vision, camera networks and non-classical cameras - OMNIVIS.
15. Hadj-Abdelkader, H., Malis, E., & Rives, P. (2008). Spherical image processing for accurate visual odometry with omnidirectional cameras. In Workshop on omnidirectional vision, camera networks and non-classical cameras - OMNIVIS.
16. Hansen, P., Corke, P., Boles, W., & Daniilidis, K. (2007a). Scale invariant feature matching with wide angle images. In Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 1668-1694). doi:10.1109/IROS.2007.4399266.
17. Hansen, P., Corke, P., Boles, W., & Daniilidis, K. (2007b). Scaleinvariant features on the sphere. In International conference on computer vision (pp. 1-8). doi:10.1109/ICCV.2007.4408893.
18. Harris, C., & Stephens, M. J. (1988). A combined corner and edge detector. In Alvey conference (pp. 147-152). http://www.csse.uwa.edu.au/~pk/ Research/MatlabFns/Spatial/Docs/Harris/A-Combined-Corner-and-Edge-Detector.pdf.
19. Kadir, T., & Brady, M. (2001). Saliency, scale and image description. International Journal of Computer Vision, 45(2), 83-105. doi:10.1023/A: 1012460413855. (Pubitemid 33125858)
20. Lindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30(2), 79-116. doi:10.1023/A: 1008045108935. (Pubitemid 128517917)
21. Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2), 91-110. doi:10.1023/B:VISI.0000029664.99615.94.
22. Matas, J., Chum, O., Urba, M., & Pajdla, T. (2002). Robust wide baseline stereo from maximally stable extremal regions. In Proceedings of the British machine vision conference (pp. 384-393).
23. Mauthner, T., Fraundorfer, F., & Bischof, H. (2006). Region matching for omnidirectional images using virtual camera planes. In Proceedings of the computer vision winter workshop 2006.
24. Menegatti, E., Pretto, A., Scarpa, A., & Pagello, E. (2006). Omnidirectional vision scan matching for robot localization in dynamic environments. IEEE Transactions on Robotics, 22(3), 523-535. (Pubitemid 43898872)
25. Mikolajczyk, K., & Schmid, C. (2005). A performance evaluation of local descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(10), 1615-1630. doi:10.1109/TPAMI.2005.188. (Pubitemid 41555406)
26. Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., & van Gool, L. (2005). A comparison of affine region detectors. International Journal of Computer Vision, 65(1), 43-72. doi:10.1007/s11263-005-3848-x. (Pubitemid 43281159)
27. Rodrigues, O. (1840). Des lois géométriques qui régissent les déplacements d'un système solide dans l'espace, et de la variation des coordonnées provenant de ces déplacements considérés indépendamment des causes qui peuvent les produire. Journal de Mathématiques Pures et Appliquées, 5, 380-440.
28. Scaramuzza, D., & Siegwart, R. (2008). Appearance-guided monocular omnidirectional visual odometry for outdoor ground vehicles. IEEE Transactions on Robotics, 24(5), 1015-1026.
29. Sirmacek, B., & Unsalan, C. (2009). Urban-area and building detection using sift keypoints and graph theory. IEEE Transactions on Geoscience and Remote Sensing, 47(4), 1156-1167. doi:10.1109/TGRS.2008.2008440.
30. Smith, S. M., & Brady, J. M. (1997). Susan - a new approach to low level image processing. International Journal of Computer Vision, 23, 45-78. (Pubitemid 127717027)
31. Tamimi, H., Andreasson, H., Treptow, A., Duckett, T., & Zell, A. (2006). Localization of mobile robots with omnidirectional vision using particle filter and iterative sift. Robotics and Autonomous Systems, 54(9), 758-765. doi:10.1016/j.robot.2006.04.018. http://www.sciencedirect.com/science/article/ B6V16-4KJ0SSH-1/2/a0cb5ac27fe99eec909f6767d486baa2. Selected papers from the 2nd European Conference on Mobile Robots (ECMR '05). (Pubitemid 44205435)
32. Tosic, I., & Frossard, P. (2009). Spherical imaging in omnidirectional camera networks. In Multi-camera networks: concepts and applications.
33. Tuytelaars, T., & Mikolajczyk, K. (2007). Local invariant feature detectors: a survey. Foundations and Trends in Computer Graphics and Vision, 3(3), 177-280. doi:10.1561/0600000017.
34. Tygert, M. (2008). Fast algorithms for spherical harmonic expansions, II. Journal of Computational Physics, 227(8), 4260-4279. doi:10.1016/j.jcp.2007.12. 019.
35. Valgren, C., & Lilienthal, A. (2007). SIFT, SURF and seasons: longterm outdoor localization using local features. In Proceedings of the European conference on mobile robots (ECMR).
36. Van Gool, L. J., Moons, T., & Ungureanu, D. (1996). Affine/photometric invariants for planar intensity patterns. In Computer vision - ECCV'96 (pp. 642-651). doi:10.1007/BFb0015574. (Pubitemid 126064360)
37. Vedaldi, A., & Fulkerson, B. (2008) VLFeat: an open and portable library of computer vision algorithms. http://www.vlfeat.org/
38. Vincenty, T. (1975). Direct and inverse solutions of geodesics on the ellipsoid with application of nested equations. Survey Review, XXIII(176), 88-93.
39. Yuen, D., & MacDonald, B. (2005). Vision-based localization algorithm based on landmark matching, triangulation, reconstruction, and comparison. IEEE Transactions on Robotics, 21(2), 217-226. doi:10.1109/TRO.2004.835452. (Pubitemid 40608452)
40. Zabih, R., & Woodfill, J. (1994). Non-parametric local transforms for computing visual correspondence. In Lecture notes in computer science. Computer vision - ECCV'94 (pp. 151-158). Berlin: Springer. doi:10.1007/BFb0028329.