Empirical Evaluation of Dissimilarity Measures for Color and Texture
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Image Retrieval from the World Wide Web: Issues, Techniques, and Systems
ACM Computing Surveys (CSUR)
Generative versus Discriminative Methods for Object Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining Generative Models and Fisher Kernels for Object Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
LOCUS: Learning Object Classes with Unsupervised Segmentation
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Content-based image retrieval by using tree-structured features and multi-layer self-organizing map
Pattern Analysis & Applications
Image indexing and retrieval based on vector quantization
Pattern Recognition
Features for image retrieval: an experimental comparison
Information Retrieval
Indexing structures for content-based retrieval of large image databases: a review
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
Shape-based image retrieval in botanical collections
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
IEEE Transactions on Multimedia
Image classification for content-based indexing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Bagging Constraint Score for feature selection with pairwise constraints
Pattern Recognition
A novel image retrieval model based on the most relevant features
Knowledge-Based Systems
Active SVM-based relevance feedback using multiple classifiers ensemble and features reweighting
Engineering Applications of Artificial Intelligence
Deriving kernels from generalized Dirichlet mixture models and applications
Information Processing and Management: an International Journal
Weighted Association Rule Mining for Video Semantic Detection
International Journal of Multimedia Data Engineering & Management
Expert Systems with Applications: An International Journal
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In this paper, we propose a probabilistic framework for efficient retrieval and indexing of image collections. This framework uncovers the hierarchical structure underlying the collection from image features based on a hybrid model that combines both generative and discriminative learning. We adopt the generalized Dirichlet mixture and maximum likelihood for the generative learning in order to estimate accurately the statistical model of the data. Then, the resulting model is refined by a new discriminative likelihood that enhances the power of relevant features. Consequently, this new model is suitable for modeling high-dimensional data described by both semantic and low-level (visual) features. The semantic features are defined according to a known ontology while visual features represent the visual appearance such as color, shape, and texture. For validation purposes, we propose a new visual feature which has nice invariance properties to image transformations. Experiments on the Microsoft's collection (MSRCID) show clearly the merits of our approach in both retrieval and indexing.