Large-Scale Image Geo-Localization Using Dominant Sets

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 41, Issue 1, 2019, Pages 148-161

  Zemene, Eyasu ^a,b   Tesfaye, Yonatan Tariku ^b,c   Idrees, Haroon ^b   Prati, Andrea ^d   Pelillo, Marcello ^a   Shah, Mubarak ^b  

^a CA' FOSCARI UNIVERSITY OF VENICE   (Italy)

^b UNIVERSITY OF CENTRAL FLORIDA   (United States)

^c UNIVERSITY IUAV OF VENICE   (Italy)

^d UNIVERSITY OF PARMA   (Italy)

Author keywords

constrained dominant set; dominant set clustering; Geo localization; multiple nearest neighbor feature matching

Indexed keywords

COMPUTER VISION; DATABASE SYSTEMS; FLOW VISUALIZATION; HEURISTIC METHODS; NEAREST NEIGHBOR SEARCH; QUERY PROCESSING; ROBUSTNESS (CONTROL SYSTEMS);

DOMINANT SET; DOMINANT SET CLUSTERING; FEATURE MATCHING; FLICKR; GEO-LOCALIZATION; GOOGLE;

GLOBAL POSITIONING SYSTEM;

EID: 85040076695     PISSN: 01628828     EISSN: 19393539     Source Type: Journal    
DOI: 10.1109/TPAMI.2017.2787132     Document Type: Article

References (55)

1. A. R. Zamir and M. Shah, "Accurate image localization based on google maps street view," in Proc. Eur. Conf. Comput. Vis., 2010, pp. 255-268.
2. A. R. Zamir and M. Shah, "Image Geo-localization based on multiple nearest neighbor feature matching using generalized graphs," IEEE Trans. Pattern Anal. Mach. Intell., vol. 36, no. 8, pp. 1546-1558, Aug. 2014.
3. J. Hays and A. A. Efros, "Im2gps: estimating geographic information from a single image," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2008, pp. 1-8.
4. G. Schindler, M. A. Brown, and R. Szeliski, "City-scale location recognition," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., 2007, pp. 1-7.
5. S. RotaBulo and I. M. Bomze, "Infection and immunization: A new class of evolutionary game dynamics," Games Econom. Behavior, vol. 71, no. 1, pp. 193-211, 2011.
6. S. R. Bulo, M. Pelillo, and I. M. Bomze, "Graph-based quadratic optimization: A fast evolutionary approach," Comput. Vis. Image Understanding, vol. 115, no. 7, pp. 984-995, 2011.
7. Y. Avrithis, Y. Kalantidis, G. Tolias, and E. Spyrou, "Retrieving landmark and non-landmark images from community photo collections," in Proc. 18th ACM Int. Conf. Multimedia, 2010, pp. 153-162.
8. D. M. Chen, et al., "City-scale landmark identification on mobile devices," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2011, pp. 737-744.
9. T. Quack, B. Leibe, and L. Van Gool, "World-scale mining of objects and events from community photo collections," in Proc. Int. Conf. Content-Based Image Video Retrieval, 2008, pp. 47-56.
10. Y.-T. Zheng, et al., "Tour the world: building a web-scale landmark recognition engine," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2009, pp. 1085-1092.
11. H. Jin Kim, E. Dunn, and J.-M. Frahm, "Predicting good features for image geo-localization using per-bundle vlad," in Proc. IEEE Int. Conf. Comput. Vis., 2015, pp. 1170-1178.
12. J. Hays and A. A. Efros, "Large-scale image geolocalization," in Multimodal Location Estimation of Videos and Images. Berlin, Germany: Springer, 2015, pp. 41-62.
13. T. Weyand, I. Kostrikov, and J. Philbin, "Planet-photo geolocation with convolutional neural networks," ECCV, pp. 37-55, 2016.
14. D. J. Crandall, L. Backstrom, D. Huttenlocher, and J. Kleinberg, "Mapping the worlds photos," in Proc. 18th Int. Conf. World Wide Web, 2009, pp. 761-770.
15. T. Sattler, M. Havlena, K. Schindler, and M. Pollefeys, "Largescale location recognition and the geometric burstiness problem," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2016, pp. 1582-1590.
16. R. Arandjelovic, P. Gronat, A. Torii, T. Pajdla, and J. Sivic, "Netvlad: CNN architecture for weakly supervised place recognition," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2016, pp. 5297-5307.
17. A. Torii, J. Sivic, M. Okutomi, and T. Pajdla, "Visual place recognition with repetitive structures," IEEE Trans. Pattern Anal. Mach. Intell., vol. 37, no. 11, pp. 2346-2359, Nov. 2015.
18. B. Zeisl, T. Sattler, and M. Pollefeys, "Camera pose voting for large-scale image-based localization," in Proc. IEEE Int. Conf. Comput. Vis., 2015, pp. 2704-2712.
19. S. Agarwal, N. Snavely, I. Simon, S. M. Seitz, and R. Szeliski, "Building rome in a day," in Proc. IEEE 12th Int. Conf. Comput. Vis., 2009, pp. 72-79.
20. Y. Li, N. Snavely, D. Huttenlocher, and P. Fua, "Worldwide pose estimation using 3d point clouds," in Proc. Eur. Conf. Comput. Vis., 2012, pp. 15-29.
21. T. Sattler, B. Leibe, and L. Kobbelt, "Improving image-based localization by active correspondence search," in Proc. Eur. Conf. Comput. Vis., 2012, pp. 752-765.
22. E.Kalogerakis,O.Vesselova, J.Hays,A.A. Efros, and A.Hertzmann, "Image sequence geolocation with human travel priors," in Proc. IEEE 12th Int. Conf. Comput. Vis., 2009, pp. 253-260.
23. G. Vaca-Castano, A. R. Zamir, and M. Shah, "City scale geospatial trajectory estimation of a moving camera," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2012, pp. 1186-1193.
24. A. Hakeem, R. Vezzani, M. Shah, and R. Cucchiara, "Estimating geospatial trajectory of a moving camera," in Proc. 18th Int. Conf. Pattern Recognit., 2006, pp. 82-87.
25. C.-Y. Chen and K. Grauman, "Clues from the beaten path: Location estimation with bursty sequences of tourist photos," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2011, pp. 1569-1576.
26. T.-Y. Lin, S. Belongie, and J. Hays, "Cross-view image geolocalization," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2013, pp. 891-898.
27. T.-Y. Lin, Y. Cui, S. Belongie, and J. Hays, "Learning deep representations for ground-to-aerial geolocalization," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2015, pp. 5007-5015.
28. S. Workman, R. Souvenir, and N. Jacobs, "Wide-area image geolocalization with aerial reference imagery," in Proc. IEEE Int. Conf. Comput. Vis., 2015, pp. 3961-3969.
29. N. Jacobs, S. Satkin, N. Roman, R. Speyer, and R. Pless, "Geolocating static cameras," in Proc. IEEE 11th Int. Conf. Comput. Vis., 2007, pp. 1-6.
30. S. Ramalingam, S. Bouaziz, P. Sturm, and M. Brand, "Skyline2gps: Localization in urban canyons using omni-skylines," in Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst., 2010, pp. 3816-3823.
31. R. Arandjelovic and A. Zisserman, "Dislocation: Scalable descriptor distinctiveness for location recognition," in Proc. Asian Conf. Comput. Vis., 2014, pp. 188-204.
32. A. Bergamo, S. N. Sinha, and L. Torresani, "Leveraging structure from motion to learn discriminative codebooks for scalable landmark classification," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2013, pp. 763-770.
33. S. Cao and N. Snavely, "Graph-based discriminative learning for location recognition," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2013, pp. 700-707.
34. P. Gronat, G. Obozinski, J. Sivic, and T. Pajdla, "Learning and calibrating per-location classifiers for visual place recognition," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2013, pp. 907-914.
35. Q. Hao, R. Cai, Z. Li, L. Zhang, Y. Pang, and F. Wu, "3d visual phrases for landmark recognition," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2012, pp. 3594-3601.
36. M. Muja and D. G. Lowe, "Fast approximate nearest neighbors with automatic algorithm configuration," in Proc. 4th Int. Conf. Comput. Vis. Theory Appl., 2009, pp. 331-340.
37. M. Pavan and M. Pelillo, "Dominant sets and pairwise clustering," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 1, pp. 167-172, Jan. 2007.
38. Y. T. Tesfaye, E. Zemene, M. Pelillo, and A. Prati, "Multi-object tracking using dominant sets," IET Comput. Vis., vol. 10, pp. 289-298, 2016.
39. S. Vascon, E. Z. Mequanint, M. Cristani, H. Hung, M. Pelillo, and V. Murino, "Detecting conversational groups in images and sequences: A robust game-theoretic approach," Comput. Vis. Image Understanding, vol. 143, pp. 11-24, 2016.
40. R. Horst, P. Pardalos, and N. Van Thoai, Introduction to Global Optimization. Dordrecht/Boston/London: Kluwer Academic Publishers, 2000.
41. I. M. Bomze, "On standard quadratic optimization problems," J. Global Optimization, vol. 13, no. 4, pp. 369-387, 1998.
42. I. M. Bomze, "Evolution towards the maximum clique," J. Global Optimization, vol. 10, no. 2, pp. 143-164, 1997.
43. M. Pelillo, "Replicator dynamics in combinatorial optimization," in Encyclopedia of Optimization, 2nd Ed. New York, NY, USA: Springer US, 2009, pp. 3279-3291.
44. S. Todorovic and N. Ahuja, "Region-based hierarchical image matching," Int. J. Comput. Vis., vol. 78, no. 1, pp. 47-66, 2008.
45. M. Pavan and M. Pelillo, "Dominant sets and hierarchical clustering," in Proc. 9th IEEE Int. Conf. Comput. Vis., 2003, pp. 362-369.
46. E. Zemene and M. Pelillo, "Interactive image segmentation using constrained dominant sets," in Proc. Eur. Conf. Comput. Vis., 2016, pp. 278-294.
47. A. Oliva and A. Torralba, "Modeling the shape of the scene: A holistic representation of the spatial envelope," Int. J. Comput. Vis., vol. 42, no. 3, pp. 145-175, 2001.
48. K. Simonyan and A. Zisserman, "Very deep convolutional networks for large-scale image recognition," CoRR, vol. abs/1409.1556, 2014.
49. L. Zheng, S. Wang, L. Tian, F. He, Z. Liu, and Q. Tian, "Queryadaptive late fusion for image search and person re-identification," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2015, pp. 1741-1750.
50. S. Zhang, M. Yang, T. Cour, K. Yu, and D. N. Metaxas, "Query specific rank fusion for image retrieval," IEEE Trans. Pattern Anal. Mach. Intell., vol. 37, no. 4, pp. 803-815, Apr. 2015.
51. G. Tolias, R. Sicre, and H. Jegou, "Particular object retrieval with integral max-pooling of CNN activations," in Proc. Int. Conf. Learning Representations, 2016.
52. F. Radenovic, G. Tolias, and O. Chum, "CNN image retrieval learns from bow: Unsupervised fine-tuning with hard examples," in Proc. 14th Eur. Conf. Comput. Vis., 2016, pp. 3-20.
53. D. M. Chen, et al., "City-scale landmark identification on mobile devices," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2011, pp. 737-744.
54. G. Tolias, Y. S. Avrithis, and H. Jegou, "Image search with selective match kernels: Aggregation across single and multiple images," Int. J. Comput. Vis., vol. 116, no. 3, pp. 247-261, 2016.
55. H. Jegou, M. Douze, and C. Schmid, "Product quantization for nearest neighbor search," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 1, pp. 117-128, Jan. 2011.