Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Bridging the semanitic gap in image retrieval
Distributed multimedia databases
Improving Text Classification by Shrinkage in a Hierarchy of Classes
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Hierarchical document categorization with support vector machines
Proceedings of the thirteenth ACM international conference on Information and knowledge management
IEEE Transactions on Pattern Analysis and Machine Intelligence
Classification of user image descriptions
International Journal of Human-Computer Studies
Automatic Face Recognition for Film Character Retrieval in Feature-Length Films
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Evaluating the impact of selection noise in community-based web search
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Large Margin Methods for Structured and Interdependent Output Variables
The Journal of Machine Learning Research
Multimedia Annotations on the Semantic Web
IEEE MultiMedia
Estimating the Support of a High-Dimensional Distribution
Neural Computation
Content-based multimedia information retrieval: State of the art and challenges
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Hierarchical classification: combining Bayes with SVM
ICML '06 Proceedings of the 23rd international conference on Machine learning
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 Dependent Regions for Object Categorization in a Generative Framework
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
MILES: Multiple-Instance Learning via Embedded Instance Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-time computerized annotation of pictures
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
A survey of content-based image retrieval with high-level semantics
Pattern Recognition
International Journal of Computer Vision
Incremental Algorithms for Hierarchical Classification
The Journal of Machine Learning Research
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ontology driven content based image retrieval
Proceedings of the 6th ACM international conference on Image and video retrieval
Predicting Structured Data (Neural Information Processing)
Predicting Structured Data (Neural Information Processing)
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Sampling strategies for bag-of-features image classification
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Semantic hierarchies for image annotation: A survey
Pattern Recognition
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We address the problem of describing precisely an object present in an image. The starting point is a semantic lattice defining all possible coherent object descriptions through inheritance and exclusion relations. This domain knowledge is used in a learning process which outputs a set of coherent explanations of the image valued by their confidence level. Our first contribution is to design this method for multiple complexity level image description. Our secondary focus is to develop rigorous evaluation standards for this computer vision task which, to our knowledge, has not been addressed in the literature despite its possible use in symbolic annotation of multimedia database. A critical evaluation of our approach under the proposed standards is presented on a new appropriate car database that we have collected.