Joint categorization of queries and clips for web-based video search
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Image annotation by hierarchical mapping of features
Proceedings of the 16th international conference on World Wide Web
Content-based object movie retrieval and relevance feedbacks
EURASIP Journal on Advances in Signal Processing
Semantic image classification using statistical local spatial relations model
Multimedia Tools and Applications
Improving Web search using image snippets
ACM Transactions on Internet Technology (TOIT)
A survey of browsing models for content based image retrieval
Multimedia Tools and Applications
Annotating personal albums via web mining
MM '08 Proceedings of the 16th ACM international conference on Multimedia
TSVM-HMM: Transductive SVM based hidden Markov model for automatic image annotation
Expert Systems with Applications: An International Journal
Learning instance specific distances using metric propagation
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Semi-supervised learning with very few labeled training examples
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Semi-supervised topic modeling for image annotation
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Integrating visual and semantic contexts for topic network generation and word sense disambiguation
Proceedings of the ACM International Conference on Image and Video Retrieval
Multimodal image retrieval via Bayesian information fusion
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Modeling, classifying and annotating weakly annotated images using Bayesian network
Journal of Visual Communication and Image Representation
Multi modal semantic indexing for image retrieval
Proceedings of the ACM International Conference on Image and Video Retrieval
Vicept: link visual features to concepts for large-scale image understanding
Proceedings of the international conference on Multimedia
Variational inference with graph regularization for image annotation
ACM Transactions on Intelligent Systems and Technology (TIST)
Modeling continuous visual features for semantic image annotation and retrieval
Pattern Recognition Letters
Multimedia data mining: state of the art and challenges
Multimedia Tools and Applications
Integrating hierarchical feature selection and classifier training for multi-label image annotation
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Mining partially annotated images
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
A review on automatic image annotation techniques
Pattern Recognition
Exploiting the entire feature space with sparsity for automatic image annotation
MM '11 Proceedings of the 19th ACM international conference on Multimedia
A survey of semantic multimedia retrieval systems
MACMESE'11 Proceedings of the 13th WSEAS international conference on Mathematical and computational methods in science and engineering
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
A unified context model for web image retrieval
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Interactive tool for image annotation using a semi-supervised and hierarchical approach
Computer Standards & Interfaces
A Probabilistic SVM Approach to Annotation of Calcification Mammograms
International Journal of Digital Library Systems
Using Hilbert scan on statistical color space partitioning
Computers and Electrical Engineering
Learning semantic concepts from image database with hybrid generative/discriminative approach
Engineering Applications of Artificial Intelligence
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This paper addresses automatic image annotation problem and its application to multi-modal image retrieval. The contribution of our work is three-fold. (1) We propose a probabilistic semantic model in which the visual features and the textual words are connected via a hidden layer which constitutes the semantic concepts to be discovered to explicitly exploit the synergy among the modalities. (2) The association of visual features and textual words is determined in a Bayesian framework such that the confidence of the association can be provided. (3) Extensive evaluation on a large-scale, visually and semantically diverse image collection crawled from Web is reported to evaluate the prototype system based on the model. In the proposed probabilistic model, a hidden concept layer which connects the visual feature and the word layer is discovered by fitting a generative model to the training image and annotation words through an Expectation-Maximization (EM) based iterative learning procedure. The evaluation of the prototype system on 17,000 images and 7,736 automatically extracted annotation words from crawled Web pages for multi-modal image retrieval has indicated that the proposed semantic model and the developed Bayesian framework are superior to a state-of-the-art peer system in the literature.