Subspace learning-based dimensionality reduction in building recognition

Neurocomputing

Volumn 73, Issue 1-3, 2009, Pages 324-330

  Li, Jing ^a   Allinson, Nigel M ^a  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

Biologically inspired feature extraction; Building recognition; Dimensionality reduction; Gist features; Subspace learning

Indexed keywords

BIOLOGICALLY-INSPIRED FEATURE EXTRACTION; BUILDING RECOGNITION; DIMENSIONALITY REDUCTION; GIST FEATURES; SUBSPACE LEARNING;

BUILDINGS; COMPUTER VISION; DISCRIMINANT ANALYSIS; EDUCATION; FACE RECOGNITION; FEATURE EXTRACTION; OBJECT RECOGNITION; PRINCIPAL COMPONENT ANALYSIS;

LEARNING ALGORITHMS;

ARTICLE; COLOR DISCRIMINATION; CONTROLLED STUDY; DISCRIMINANT ANALYSIS; ILLUMINATION; INFORMATION PROCESSING; LEARNING; LEARNING ALGORITHM; MATHEMATICAL ANALYSIS; ORIENTATION; PATTERN RECOGNITION; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; ROTATION; TASK PERFORMANCE;

EID: 70449526569     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2009.08.016     Document Type: Article

References (55)

1. Ali H., Paar G., and Paletta L. Semantic Indexing for visual recognition of buildings. Proc. Int. Symp. Mobile Mapp. Technol. (2007) 28-31
2. Belkin M., and Niyogi P. Laplacian eigenmaps and spectral techniques for embedding and clustering. Adv. Neural Inf. Process. Syst. 14 (2002) 585-591
3. Bellman R. Adaptive Control Processes: A Guided Tour (1961), Princeton University Press, Princeton, NJ
4. Cai D., He X., and Han J. Semi-supervised discriminant analysis, computer vision. Proc. IEEE 11th Int. Conf. Comput. Vision (2007) 1-7
5. D. Cai, X. He, J. Han, Using Graph Model for Face Analysis, Technical Report no. 2636, Department of Computer Science, University of Illinois at Urbana-Champaign, 2005.
6. Cover T., and Hart P. Nearest neighbor pattern classification. IEEE Trans. Inf. Theory IT-13 1 (1967) 21-27
7. Daugman J.G. Two-dimensional spectral analysis of cortical receptive field profile. Vision Res. 20 (1980) 847-856
8. Daugman J.G. Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. J. Opt. Soc. Am. 2 7 (1985) 1160-1169
9. Dorko G., and Schmid C. Selection of scale-invariant parts for object class recognition. Proc. IEEE Int. Conf. Comput. Vision 1 (2003) 634-639
10. Fergus R., Perona P., and Zisserman A. Object class recognition by unsupervised scale-invariant learning. Proc. IEEE Conf. Comput. Vision Pattern Recognition 2 (2003) 264-271
11. Ferraril V., Tuytelaars T., and Gool L.V. Simultaneous Object Recognition and Segmentation by Image Exploration, Lecture Notes in Computer Science vol. 4170 (2006), Springer pp. 145-169
12. Fritz G., Seifert C., and Paletta L. Urban object recognition from informative local features. Proc. IEEE Int. Conf. Robotics Autom. (2005) 131-137
13. C. Harris, M. Stephens, A Combined Corner and Edge Detector, in: Alvey Vision Conf., 1988, pp. 147-151.
14. He X., Cai D., Wen J., Ma W., and Zhang H. Clustering and searching WWW images using link and page layout analysis. ACM Trans. Multimedia Comput., Commun. Appl. 3 2 (2007)
15. He X., Cai D., and Han J. Learning a maximum margin sub-space for image retrieval. IEEE Trans. Knowl. Data Eng. 20 2 (2008) 189-201
16. X. He, P. Niyogi, Locality Preserving Projections, in: Proc. Conf. Advances in Neural Information Processing Systems, 2003.
17. Hutchings R., and Mayol-Cuevas W. Building Recognition for Mobile Devices: Incorporating Positional Information with Visual Features, CSTR-06-017, Computer Science (2005), University of Bristol
18. Iqbal Q., and Aggarwall J.K. Applying perceptual grouping to content-based image retrieval: building images. Proc. IEEE Conf. Comput. Vision Pattern Recognition 1 (1999) 42-48
19. Itti L., Koch C., and Niebur E. A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20 11 (1998) 1,254-1,259
20. Jolliffe I.T. Principal Component Analysis. 2nd Ed. (2002), Springer
21. Lazebnik S., Schmid C., and Ponce J. Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. Proc. IEEE Conf. Comput. Vision Pattern Recognition 2 (2006) 2169-2178
22. Lee T.S. Image representation using 2D gabor wavelets. IEEE Trans. Pattern Anal. Mach. Intell. 18 10 (2003) 959-971
23. Leibe B., and Schiele B. Interleaved object categorization and segmentation. Proc. Br. Mach. Vision Conf. (2003) 759-768
24. Leung T., and Malik J. Representing and recognizing the visual appearance of materials using three-dimensional textons. Int. J. Comput. Vision 43 1 (2001) 29-44
25. Li F.-F., Fergus R., and Perona P. A bayesian approach to unsupervised one-shot learning of object categories. Proc. IEEE Int. Conf. Comput. Vision 2 (2003) 1134-1141
26. Li J., and Allinson N.M. A comprehensive review of current local features for computer vision. Neurocomputing 71 10-12 (2008) 1771-1787
27. Li Y., and Shapiro L.G. Consistent line clusters for building recognition in CBIR. Proc. IEEE Int. Conf. Pattern Recognition 3 (2002) 952-956
28. Lowe D.G. Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60 2 (2004) 91-110
29. Marcelja S. Mathematical description of the responses of simple cortical cells. J. Opt. Soc. Am. 70 11 (1980) 1297-1300
30. McLachlan G.J. Discriminant Analysis and Statistical Pattern Recognition (1992), Wiley-Interscience, New York
31. Mikolajczyk K., Leibe B., and Schiele B. Local features for object class recognition. Proc. IEEE Int. Conf. Comput. Vision 2 (2005) 1792-1799
32. Oliva A., and Torralba A. Modeling the shape of the scene: a holistic representation of the spatial envelope. Int. J. Comput. Vision 42 3 (2001) 145-175
33. Roweis S.T., and Saul L.K. Nonlinear dimensionality reduction by locally linear embedding. Science 290 (2000) 2,323-2,326
34. Siagian C., and Itti L. Rapid biologically-inspired scene classification using features shared with visual attention. IEEE Trans. Pattern Anal. Mach. Intell. 29 2 (2007) 300-312
35. D. Song, D. Tao, Biologically Inspired Feature Manifold for Scene Classification, IEEE Trans. Image Processing, to appear.
36. Song D., and Tao D. C1 units for scene classification. Proc. IEEE Int. Conf. Pattern Recognition (2008) 1-4
37. Tao D., Li X., Wu X., and Maybank S.J. General tensor discriminant analysis and gabor features for gait recognition. IEEE Trans. Pattern Anal. Mach. Intell. 29 10 (2007) 1700-1715
38. Tao D., Li X., Wu X., and Maybank S.J. Geometric mean for subspace selection. IEEE Trans. Pattern Anal. Mach. Intell. 31 2 (2009) 260-274
39. Tao D., Li X., and Maybank S.J. Negative samples analysis in relevance feedback. IEEE Trans. Knowl. Data Eng. 19 4 (2007) 568-580
40. Tao D., and Tang X. Nonparametric discriminant analysis in relevance feedback for content-based image retrieval. Proc. IEEE Int. Conf. Pattern Recognition (2004) 1013-1016
41. Tao D., Tang X., and Li X. Which components are important for interactive image searching?. IEEE Trans. Circuits Syst. Video Technol. 18 1 (2008) 1-11
42. Tao D., Tang X., Li X., and Rui Y. Kernel direct biased discriminant analysis: a new content-based image retrieval relevance feedback algorithm. IEEE Trans. Multimedia 8 4 (2006) 716-727
43. Tenenbaum J., Silva V., and Langford J. A global geometric framework for nonlinear dimensionality reduction. Science 290 (2000) 2319-2323
44. Torralba A., Murphy K.P., Freeman W.T., and Rubin M.A. Context-based vision system for place and object recognition. Proc. IEEE Int. Conf. Comput. Vision 1 (2003) 273-280
45. Treisman A., and Gelade G. A feature-integration theory of attention. Cognitive Psychol. 12 (1980) 97-137
46. Turner R.S. In the Eye's Mind: Vision and the Helmholtz Hering Controversy (1994), Princeton University Press
47. Ullah M.M., Pronobis A., Caputo B., Luo J., Jensfelt R., and Christensen H.I. Towards robust place recognition for robot localization. IEEE Int. Conf. Robotics Autom. (2008) 530-537
48. Varma M., and Zisserman A. A statistical approach to texture classification from single images. Int. J. Comput. Vision 62 1-2 (2005) 61-81
49. Wu J., and Rehg J.M. Where am I: place instance and category recognition using spatial PACT. Proc. IEEE Conf. Comput. Vision Pattern Recognition (2008) 1-8
50. Xu D., Lin S., Yan S., and Tang X. Rank-one projections with adaptive margin for face recognition. IEEE Trans. Syst., Man Cybernetics, Part B 37 5 (2007) 1226-1236
51. Yan S., Xu D., Yang Q., Zhang L., Tang X., and Zhang H. Mul-tilinear discriminant analysis for face recognition. IEEE Trans. Image Process. 16 1 (2007) 212-220
52. Zhang T., Tao D., and Yang J. Discriminative locality alignment. Proc. Eur. Conf. Comput. Vision (2008) 725-738
53. Zhang T., Tao D., Li X., and Yang J. A unifying framework for spectral analysis based dimensionality reduction. Proc. IEEE Int. Joint Conf. Neural Networks (2008) 1,671-1,678
54. T. Zhang, D. Tao, X. Li, J. Yang, Patch Alignment for Dimensionality Reduction, IEEE Trans. Knowledge and Data Engineering, 2008.
55. Zhang W., and Kosecka J. Localization based on building recognition. IEEE Workshop Appl. Visually Impaired (2005) 21-28