Building recognition in urban environments: A survey of state-of-the-art and future challenges

Information Sciences

Volumn 277, Issue , 2014, Pages 406-420

  Li, Jing ^a   Huang, Wei ^a   Shao, Ling ^b   Allinson, Nigel ^c  

^a NANCHANG UNIVERSITY   (China)

^b UNIVERSITY OF SHEFFIELD   (United Kingdom)

^c UNIVERSITY OF LINCOLN   (United Kingdom)

Author keywords

Building recognition; Dimensionality reduction; Robot localization; SIFT; Visual navigation; Wide baseline matching

Indexed keywords

CLUSTERING ALGORITHMS; IMAGE MATCHING; ROBOT APPLICATIONS; SURVEYS; URBAN PLANNING;

BUILDING RECOGNITION; DIMENSIONALITY REDUCTION; ROBOT LOCALIZATION; SIFT; VISUAL NAVIGATION; WIDE-BASELINE MATCHING;

BUILDINGS;

EID: 84901757467     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2014.02.112     Document Type: Article

References (63)

1. S. Agarwal, Y. Furukawa, N. Snavely, B. Curless, S.M. Seitz, and R. Szeliski Reconstructing Rome IEEE Comput. 43 6 2010 40 47
2. H. Ali, G. Paar, L. Paletta, Semantic indexing for visual recognition of buildings, in: Proc. Int'l. Symposium on Mobile Mapping Technology, 2007, pp. 28-31.
3. R. Baeza-Yates, and B. Ribeiro-Neto Modern Information Retrieval 1999 ACM Press ISBN: 020139829
4. M. Belkin, and P. Niyogi Laplacian eigenmaps and spectral techniques for embedding and clustering Adv. Neural Inform. Process. Syst. 14 2002 585 591
5. R. Bellman Adaptive Control Processes: A Guided Tour 1961 Princeton University Press Princeton, NJ
6. J.L. Bentley Multidimensional binary search trees used for associative searching Commun. ACM 18 9 1975 509 517
7. C.M. Bishop Pattern Recognition and Machine Learning 2006 Springer
8. Y-L. Boureau, J. Ponce, Y. Lecun, A theoretical analysis of feature pooling in visual recognition, in: Int'l. Conf. Machine Learning, 2010.
9. J. Canny A computational approach to edge detection IEEE Trans. Pattern Anal. Mach. Intell. 8 1986 679 698
10. Y-C. Chung, T.X. Han, Z. He, Building recognition using sketch-based representations and spectral graph matching, in: IEEE Int'l. Conf. Computer Vision, 2009.
11. T. Cover, and P. Hart Nearest neighbor pattern classification IEEE Trans. Inform. Theory 13 1 1967 21 27
12. A. Etamadi, Robust segmentation of edge data, in: Int'l. Conf. Image Processing and its Applications, 1992, pp. 311-314.
13. W. Freeman, and E. Adelson The design and use of steerable filters IEEE Trans. Pattern Anal. Mach. Intell. 13 9 1991 891 906
14. T. Goedeme, T. Tuytelaars, L.V. Gool, Fast wide baseline matching for visual navigation, in: IEEE Conf. Computer Vision and Pattern Recognition, 2004, pp. 24-29.
15. N. Groeneweg, B. Groot, A. Halma, B. Quiroga, M. Tromp, F. Groen, A fast offline building recognition application on a mobile telephone, in: Advanced Concepts for Intelligent Vision Systems, 2006, pp. 1122-1132.
16. S. Gunal, and R. Edizkan Subspace based feature selection for pattern recognition Inform. Sci. 178 19 2008 3716 3726
17. C. Harris, M. Stephens, A combined corner and edge detector, in: Alvey Vision Conf., 1988, pp. 147-151.
18. R. Hutchings, and W. Mayol-Cuevas Building Recognition for Mobile Devices: Incorporating Positional Information with Visual Features, CSTR-06-017, Computer Science 2005 University of Bristol
19. Q. Iqbal, J.K. Aggarwall, Applying perceptual grouping to content-based image retrieval: building images, in: Proc. IEEE Conf. Computer Vision and Pattern Recognition, 1999, pp. 42-48.
20. I.T. Jolliffe Principal Component Analysis second ed. 2002 Springer
21. S. Jones, and L. Shao Content-based retrieval of human actions from realistic video databases Inform. Sci. 236 2013 56 65
22. Y. Kim, K. Lee, K. Choi, S.I. Cho, Building recognition for augmented reality based navigation system, in: IEEE Int'l. Conf. Computer and Information Technology, 2006.
23. J. Li, and N.M. Allinson A comprehensive review of current local features for computer vision Neurocomputing 71 10-12 2008 1771 1787
24. J. Li, and N.M. Allinson Building recognition using local oriented features IEEE Trans. Ind. Inform. 9 3 2013 1697 1704
25. J. Li, N.M. Allinson, Relevance feedback-based building recognition, in: SPIE Visual Communications and Image Processing, vol. 7744, 2010.
26. J. Li, and N.M. Allinson Subspace learning-based dimensionality reduction in building recognition Neurocomputing 73 1-3 2009 324 330
27. J. Li, N. Allinson, D. Tao, and X. Li Multitraining support vector machine for image retrieval IEEE Trans. Image Process. 15 11 2006 3597 3601
28. Y. Li, L.G. Shapiro, Consistent line clusters for building recognition in CBIR, in: Proc. IEEE Int'l. Conf. Pattern Recognition, 2002, pp. 952-956.
29. D.G. Lowe Distinctive image features from scale-invariant keypoints Int. J. Comput. Vision 60 2 2004 91 110
30. J. Matas, O. Chum, M. Urban, T. Pajdla, Robust wide baseline stereo from maximally stable extremal regions, in: British Machine Vision Conf., 2002.
31. H. Mayer Automatic object extraction from aerial imagery - a survey focusing on buildings Comput. Vision Image Understanding 74 2 1999 138 149
32. G.J. McLachlan Discriminant Analysis and Statistical Pattern Recognition 1992 Wiley-Interscience New York
33. K. Mikolajczyk, and C. Schmid Scale & affine invariant interest point detectors Int. J. Comput. Vision 1 60 2004 63 86
34. J. Philbin, O. Chum, M. Isard, J. Sivic, A. Zisserman, Object retrieval with large vocabularies and fast spatial matching, in: IEEE Conf. Computer Vision and Pattern Recognition, 2007.
35. S.T. Roweis, and L.K. Saul Nonlinear dimensionality reduction by locally linear embedding Science 290 2000 2323 2326
36. K. Schindler, J. Bauer, A model-based method for building reconstruction, in: IEEE Int'l. Workshop on Higher-Level Knowledge in 3D Modeling and Motion, Analysis, 2003, pp. 74-82.
37. T.S.H. Shao, L.V. Gool, Zubud-Zurich buildings database for image based recognition, Technique Report No. 260, Swiss Federal Institute of Technology, 2003.
38. H. Shao, T. Svoboda, T. Tuytelaars, L.J.V. Gool, HPAT indexing for fast object/scene recognition based on local appearance, in: Int'l. Conf. Image and Video Retrieval, 2003, pp. 71-80.
39. L. Shao, T. Kadir, and M. Brady Geometric and photometric invariant distinctive regions detection Inform. Sci. 177 4 2007 1088 1122
40. C. Siagian, and L. Itti Rapid biologically-inspired scene classification using features shared with visual attention IEEE Trans. Pattern Anal. Mach. Intell. 29 2 2007 300 312
41. N. Snavely, Steven M. Seitz, and Richard Szeliski Photo tourism: exploring photo collections in 3D ACM Trans. Graph. 2006 835 846
42. W. Suleiman, T. Joliveau, E. Favier, Buildings Recognition and Camera Localization using Image Texture Description, 2011.
43. J. Tenenbaum, V. Silva, and J. Langford A global geometric framework for nonlinear dimensionality reduction Science 290 2000 2319 2323
44. A. Treisman, and G. Gelade A feature-integration theory of attention Cogn. Psychol. 12 1980 97 137
45. H. Trinh, D.-N. Kim, and K.-H. Jo Facet-based multiple building analysis for robot intelligence J. Appl. Math. Comput. 205 2 2008 537 549
46. T. Tuytelaars, Van Gool, Wide baseline stereo based on local affinely invariant regions, in: British Machine Vision Conf., 2000.
47. M.M. Ullah, A. Pronobis, B. Caputo, J. Luo, R. Jensfelt, H.I. Christensen, Towards robust place recognition for robot localization, in: IEEE Int'l. Conf. Robotics and Automation, 2008, pp. 530-537.
48. V. Vapnik The Nature of Statistical Learning Theory 1995 Springer-Verlag
49. P. Viola, M. Jones, Rapid object detection using a boosted cascade of simple features, in: Proc. of Conf. on Computer Vision and Pattern Recognition, 2001, pp. 511-518.
50. M. Xu, M. Petrou, M. Jahangiri, Component identification in the 3D model of a building, in: Int'l. Conf. Pattern Recognition, 2010, pp. 3061-3064.
51. Z-J. Zha, X-S. Hua, T. Mei, J. Wang, G-J. Qi, Z. Wang, Joint multi-label multi-instance learning for image classification, in: IEEE Conf. Computer Vision and Pattern Recognition, 2008, pp. 1-8.
52. Z-J. Zha, M. Wang, Y-T. Zheng, Y. Yang, R. Hong, and T-S. Chua Interactive video indexing with statistical active learning IEEE Trans. Multimedia 14 1 2012 17 27
53. Z-J. Zha, L. Yang, T. Mei, M. Wang, Z. Wang, Visual query suggestion, in: ACM Int'l. Conf. Multimedia, 2009, pp. 15-24.
54. Z-J. Zha, L. Yang, T. Mei, M. Wang, Z. Wang, T-S. Chua, and X-S. Hua Visual query suggestion: towards capturing user intent in internet image search ACM Trans. Multimedia Comput. Commun. Appl. 6 3 2010
55. L. Zhang, Y. Han, Y. Yang, M. Song, S. Yan, and Q. Tian Discovering discriminative graphlets for aerial image categories recognition IEEE Trans. Image Process. 22 12 2013 5071 5084
56. L. Zhang, M. Song, X. Liu, L. Sun, C. Chen, and J. Bu Recognizing architecture styles by hierarchical sparse coding of blocklets Inform. Sci. 254 2014 141 154
57. W. Zhang, and J. Košecká Hierarchical building recognition Image Vision Comput. 25 5 2007 704 716
58. Y-T. Zheng, M. Zhao, Y. Song, H. Adam, Tour the world: building a web-scale landmark recognition engine, in: IEEE Conf. Computer Vision and Pattern Recognition, 2009, pp. 1085-1092.
59. robotics.youngester.com.
60. http://web.eee.sztaki.hu/home4/.
61. apnagharit.wordpress.com.
62. www.stanford.edu.
63. http://www.flickr.com/.