Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Journal of Machine Learning Research
Multiple Bernoulli relevance models for image and video annotation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Joint visual-text modeling for automatic retrieval of multimedia documents
Proceedings of the 13th annual ACM international conference on Multimedia
Automatic video annotation by semi-supervised learning with kernel density estimation
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Exploiting spatial context constraints for automatic image region annotation
Proceedings of the 15th international conference on Multimedia
Structure-sensitive manifold ranking for video concept detection
Proceedings of the 15th international conference on Multimedia
Optimizing multi-graph learning: towards a unified video annotation scheme
Proceedings of the 15th international conference on Multimedia
A discrete direct retrieval model for image and video retrieval
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Improving Automatic Image Annotation Based on Word Co-occurrence
Adaptive Multimedial Retrieval: Retrieval, User, and Semantics
Semi-supervised kernel density estimation for video annotation
Computer Vision and Image Understanding
TSVM-HMM: Transductive SVM based hidden Markov model for automatic image annotation
Expert Systems with Applications: An International Journal
Using visual context and region semantics for high-level concept detection
IEEE Transactions on Multimedia - Special issue on integration of context and content
Improving web image retrieval using image annotations and inference network
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Thematic video thumbnail selection
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
An HMM-SVM-based automatic image annotation approach
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Ensemble multi-instance multi-label learning approach for video annotation task
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Mining multiple visual appearances of semantics for image annotation
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
EagleRank: a novel ranking model for web image search engine
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
Recognizing objects and scenes in news videos
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Multi-class particle swarm model selection for automatic image annotation
Expert Systems with Applications: An International Journal
A Probabilistic SVM Approach to Annotation of Calcification Mammograms
International Journal of Digital Library Systems
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This paper introduces a novel method for automatic annotation of images with keywords from a generic vocabulary of concepts or objects for the purpose of content-based image retrieval. An image, represented as sequence of feature-vectors characterizing low-level visual features such as color, texture or oriented-edges, is modeled as having been stochastically generated by a hidden Markov model, whose states represent concepts. The parameters of the model are estimated from a set of manually annotated (training) images. Each image in a large test collection is then automatically annotated with the a posteriori probability of concepts present in it. This annotation supports content-based search of the image-collection via keywords. Various aspects of model parameterization, parameter estimation, and image annotation are discussed. Empirical retrieval results are presented on two image-collections | COREL and key-frames from TRECVID. Comparisons are made with two other recently developed techniques on the same datasets.