Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
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
Discovering Objects and their Localization in Images
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Creating Efficient Codebooks for Visual Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
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
Object Categorization by Learned Universal Visual Dictionary
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
Scene Classification Using a Hybrid Generative/Discriminative Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Visual Search of Videos Cast as Text Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Descriptive visual words and visual phrases for image applications
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Building contextual visual vocabulary for large-scale image applications
Proceedings of the international conference on Multimedia
Towards optimal naive bayes nearest neighbor
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
CENTRIST: A Visual Descriptor for Scene Categorization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image retrieval with geometry-preserving visual phrases
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Mining discriminative co-occurrence patterns for visual recognition
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Image analysis by counting on a grid
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Randomized visual phrases for object search
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Contextual weighting for vocabulary tree based image retrieval
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Spatial pyramid co-occurrence for image classification
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Multimedia Event Detection Using Segment-Based Approach for Motion Feature
Journal of Signal Processing Systems
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The spatial layout of images plays a critical role in natural scene analysis. Despite previous work, e.g., spatial pyramid matching, how to design optimal spatial layout for scene classification remains an open problem due to the large variations of scene categories. This paper presents a novel image representation method, with the objective to characterize the image layout by various patterns, in the form of randomized spatial partition (RSP). The RSP-based image representation makes it possible to mine the most descriptive image layout pattern for each category of scenes, and then combine them by training a discriminative classifier, i.e., the proposed ORSP classifier. Besides RSP image representation, another powerful classifier, called the BRSP classifier, is also proposed. By weighting and boosting a sequence of various partition patterns, the BRSP classifier is more robust to the intra-class variations hence leads to a more accurate classification. Both RSP-based classifiers are tested on three publicly available scene datasets. The experimental results highlight the effectiveness of the proposed methods.