IEEE Transactions on Pattern Analysis and Machine Intelligence
The Random Subspace Method for Constructing Decision Forests
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
A Computationally Efficient Approach to Indoor/Outdoor Scene Classification
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Probability Estimates for Multi-class Classification by Pairwise Coupling
The Journal of Machine Learning Research
A Bayesian Hierarchical Model for Learning Natural Scene Categories
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Experimental study for the comparison of classifier combination methods
Pattern Recognition
Review: Which is the best way to organize/classify images by content?
Image and Vision Computing
A note on Platt's probabilistic outputs for support vector machines
Machine Learning
Kernel Codebooks for Scene Categorization
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Natural scene classification using overcomplete ICA
Pattern Recognition
Learning in region-based image retrieval
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
MetaXa—Context- and content-driven metadata enhancement for personal photo books
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Scene analysis by integrating primitive segmentation andassociative memory
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Reducing SVM classification time using multiple mirror classifiers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Learning semantic scene models from observing activity in visual surveillance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Face detection using spectral histograms and SVMs
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Kernel pooled local subspaces for classification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Image transform bootstrapping and its applications to semantic scene classification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An experimental bias-variance analysis of SVM ensembles based on resampling techniques
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Statistical texture characterization from discrete wavelet representations
IEEE Transactions on Image Processing
Design-based texture feature fusion using Gabor filters and co-occurrence probabilities
IEEE Transactions on Image Processing
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Human-inspired features for natural scene classification
Pattern Recognition Letters
A novel ensemble algorithm for tumor classification
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
A mass spectra-based compound-identification approach with a reduced reference library
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
| Hi-index | 0.01 |
Information in the frequency domain is useful in image classification. For natural scene classification, Oliva and Torralba proposed a global feature by sampling the power spectrum of the filtered image. In this paper, we present a hybrid global feature for scene classification. To capture the textural characteristics of the image in the frequency domain, we propose two feature extraction strategies based on gray-level co-occurrence matrices. Both contain statistics of the co-occurrence matrix, but the first one is of a much higher dimension than the second. We demonstrate that the proposed feature is a helpful supplement to the energy feature in terms of increased classification accuracy for real scene images. In order to combine these two kinds of features and further improve the classification accuracy, a posterior probability based two-stage classification method is proposed in which a linear combination of the probabilistic output of the SVMs in the first stage is used to train another SVM in the second stage. The overall results of the proposed method show an increase in the classification accuracy of about 1.5-4% compared to the original feature on four scene datasets. And the performance of the proposed method is also shown to be comparable to the recently reported results.