Support Vector Machines for 3D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Advances in kernel methods: support vector learning
Advances in kernel methods: support vector learning
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Contextual Priming for Object Detection
International Journal of Computer Vision
Indoor-Outdoor Image Classification
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
Context-based vision system for place and object recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Support Vector Machine with Local Summation Kernel for Robust Face Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
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
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
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
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Scene classification based on local autocorrelation of similarities with subspaces
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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This paper presents a scene classification method based on multiresolution orientation histogram. In recent years, some scene classification methods have been proposed because scene category information is used as the context for object detection and recognition. Recent studies uses the local parts without topological information. However, the middle size features with rough topological information are more effective for scene classification. For this purpose, we use orientation histogram with rough topological information. Since we do not the appropriate subregion size for computing orientation histogram, various subregion sizes are prepared, and multi-resolution orientation histogram is developed. Support Vector Machine is used to classify the scene category. To improve the accuracy, the similarity between orientation histogram on the same subregion is used effectively. The proposed method is evaluated with the same database and protocol as the recent studies. We confirm that the proposed method outperforms the recent scene classification methods.