Image Representation Using 2D Gabor Wavelets
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons
International Journal of Computer Vision
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Consistent Line Clusters for Building Recognition in CBIR
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Selection of Scale-Invariant Parts for Object Class Recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Context-based vision system for place and object recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Nonparametric Discriminant Analysis in Relevance Feedback for Content-Based Image Retrieval
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
A Statistical Approach to Texture Classification from Single Images
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
Local Features for Object Class Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Localization Based on Building Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Rapid Biologically-Inspired Scene Classification Using Features Shared with Visual Attention
IEEE Transactions on Pattern Analysis and Machine Intelligence
Clustering and searching WWW images using link and page layout analysis
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Negative Samples Analysis in Relevance Feedback
IEEE Transactions on Knowledge and Data Engineering
General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning a Maximum Margin Subspace for Image Retrieval
IEEE Transactions on Knowledge and Data Engineering
Geometric Mean for Subspace Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Patch Alignment for Dimensionality Reduction
IEEE Transactions on Knowledge and Data Engineering
Biologically inspired feature manifold for scene classification
IEEE Transactions on Image Processing
IEEE Transactions on Multimedia
Rank-One Projections With Adaptive Margins for Face Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
Multilinear Discriminant Analysis for Face Recognition
IEEE Transactions on Image Processing
Which Components are Important for Interactive Image Searching?
IEEE Transactions on Circuits and Systems for Video Technology
Relevance feedback for real-world human action retrieval
Pattern Recognition Letters
Multi-scale gist feature manifold for building recognition
Neurocomputing
Hi-index | 0.01 |
Building recognition is a relatively specific recognition task in object recognition, which is challenging since it encounters rotation, scaling, illumination changes, occlusion, etc. Subspace learning, which dominates dimensionality reduction, has been widely exploited in computer vision research in recent years. It consists of classical linear dimensionality reduction methods, manifold learning, etc. To explore how different subspace learning algorithms affect building recognition, some representative algorithms, i.e., principal component analysis, linear discriminant analysis, locality preserving projections (unsupervised/supervised), and semi-supervised discriminant analysis, are applied for dimensionality reduction. Moreover, a building recognition scheme based on biologically-inspired feature extraction is proposed in this paper. Experiments undertaken on our own building database demonstrate that the proposed scheme embedded with subspace learning can achieve satisfactory results.