Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
An Introduction to Variational Methods for Graphical Models
Machine Learning
Normalized Cuts and Image Segmentation
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
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Learning a Sparse Representation for Object Detection
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Features in Content-based Image Retrieval Systems: a Survey
State-of-the-Art in Content-Based Image and Video Retrieval [Dagstuhl Seminar, 5-10 December 1999]
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Multiresolution Histograms and Their Use for Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Six-Stimulus Theory for Stochastic Texture
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
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
A Comparison of Algorithms for Inference and Learning in Probabilistic Graphical Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Modeling Scenes with Local Descriptors and Latent Aspects
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Learning Object Categories from Google"s Image Search
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Categorization of natural scenes: local vs. global information
APGV '06 Proceedings of the 3rd symposium on Applied perception in graphics and visualization
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
Using Multiple Segmentations to Discover Objects and their Extent in Image Collections
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Semantic-Shift for Unsupervised Object Detection
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Robust Scene Categorization by Learning Image Statistics in Context
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Latent Layout Analysis for Discovering Objects in Images
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Semantic Modeling of Natural Scenes for Content-Based Image Retrieval
International Journal of Computer Vision
Universal and Adapted Vocabularies for Generic Visual Categorization
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image classification for content-based indexing
IEEE Transactions on Image Processing
Building global image features for scene recognition
Pattern Recognition
Stel Component Analysis: Joint Segmentation, Modeling and Recognition of Objects Classes
International Journal of Computer Vision
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Natural scene categorization from images represents a very useful task for automatic image analysis systems. In the literature, several methods have been proposed facing this issue with excellent results. Typically, features of several types are clustered so as to generate a vocabulary able to describe in a multi-faceted way the considered image collection. This vocabulary is formed by a discrete set of visual codewords whose co-occurrence and/or composition allows to classify the scene category. A common drawback of these methods is that features are usually extracted from the whole image, actually disregarding whether they derive properly from the natural scene to be classified or from foreground objects, possibly present in it, which are not peculiar for the scene. As quoted by perceptual studies, objects present in an image are not useful to natural scene categorization, indeed bringing an important source of clutter, in dependence of their size. In this paper, a novel, multi-scale, statistical approach for image representation aimed at scene categorization is presented. The method is able to select, at different levels, sets of features that represent exclusively the scene disregarding other non-characteristic, clutter, elements. The proposed procedure, based on a generative model, is then able to produce a robust representation scheme, useful for image classification. The obtained results are very convincing and prove the goodness of the approach even by just considering simple features like local color image histograms.