An automatic hierarchical image classification scheme
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Image classification and querying using composite region templates
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SMEM algorithm for mixture models
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Support vector machine active learning for image retrieval
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Indexing and retrieval of 3D models aided by active learning
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Unsupervised Learning of Finite Mixture Models
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Mean Shift: A Robust Approach Toward Feature Space Analysis
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Visually Searching the Web for Content
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Learning and inferring a semantic space from user's relevance feedback for image retrieval
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Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
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SIMPLIcity: Semantics-sensitive Integrated Matching for Picture Libraries
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CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
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Confidence-based dynamic ensemble for image annotation and semantics discovery
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On image auto-annotation with latent space models
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Probabilistic Space-Time Video Modeling via Piecewise GMM
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A probabilistic framework for semantic video indexing, filtering,and retrieval
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Image classification for content-based indexing
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A physical model-based approach to detecting sky in photographic images
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Semantics and feature discovery via confidence-based ensemble
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Mining images on semantics via statistical learning
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Using One-Class and Two-Class SVMs for Multiclass Image Annotation
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Image region entropy: a measure of "visualness" of web images associated with one concept
Proceedings of the 13th annual ACM international conference on Multimedia
Region based image annotation through multiple-instance learning
Proceedings of the 13th annual ACM international conference on Multimedia
SEVA: sensor-enhanced video annotation
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Semantic image classification with hierarchical feature subset selection
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Automatic function selection for large scale salient object detection
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Searching and browsing large scale image database using keywords and ontology
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
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Exploiting spatial context constraints for automatic image region annotation
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Mixed-initiative photo collage authoring
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Multimedia information retrieval: watershed events
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Labelling Image Regions Using Wavelet Features and Spatial Prototypes
SAMT '08 Proceedings of the 3rd International Conference on Semantic and Digital Media Technologies: Semantic Multimedia
Faceted search and retrieval based on semantically annotated product family ontology
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SEVA: Sensor-enhanced video annotation
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Semantics-preserving bag-of-words models for efficient image annotation
LS-MMRM '09 Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining
Distance metric learning from uncertain side information with application to automated photo tagging
MM '09 Proceedings of the 17th ACM international conference on Multimedia
JustClick: personalized image recommendation via exploratory search from large-scale Flickr images
IEEE Transactions on Circuits and Systems for Video Technology
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IEEE Transactions on Multimedia - Special issue on integration of context and content
An interactive approach for filtering out junk images from keyword-based google search results
IEEE Transactions on Circuits and Systems for Video Technology
Multi-modal multi-label semantic indexing of images based on hybrid ensemble learning
PCM'07 Proceedings of the multimedia 8th Pacific Rim conference on Advances in multimedia information processing
Mining large-scale news video database via knowledge visualization
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A novel approach for filtering junk images from google search results
MMM'08 Proceedings of the 14th international conference on Advances in multimedia modeling
New approach for hierarchical classifier training and multi-level image annotation
MMM'08 Proceedings of the 14th international conference on Advances in multimedia modeling
Information Processing and Management: an International Journal
Semantics-preserving bag-of-words models and applications
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Leveraging loosely-tagged images and inter-object correlations for tag recommendation
Proceedings of the international conference on Multimedia
S3MKL: scalable semi-supervised multiple kernel learning for image data mining
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Nearest-neighbor classification using unlabeled data for real world image application
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Automatic image annotation by using relevant keywords extracted from auxiliary text documents
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Distance metric learning from uncertain side information for automated photo tagging
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Integrating hierarchical feature selection and classifier training for multi-label image annotation
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IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Retrieval-based face annotation by weak label regularized local coordinate coding
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Modeling omni-directional video
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Automatic image annotation based on wordnet and hierarchical ensembles
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Salient feature selection for visual concept learning
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Semi-supervised learning for image annotation based on conditional random fields
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A unified learning framework for auto face annotation by mining web facial images
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Automatic image annotation is a promising solution to enable semantic image retrieval via keywords. In this paper, we propose a multi-level approach to annotate the semantics of natural scenes by using both the dominant image components (salient objects) and the relevant semantic concepts. To achieve automatic image annotation at the content level, we use salient objects as the dominant image components for image content representation and feature extraction. To support automatic image annotation at the concept level, a novel image classification technique is developed to map the images into the most relevant semantic image concepts. In addition, Support Vector Machine (SVM) classifiers are used to learn the detection functions for the pre-defined salient objects and finite mixture models are used for semantic concept interpretation and modeling. An adaptive EM algorithm has been proposed to determine the optimal model structure and model parameters simultaneously. We have also demonstrated that our algorithms are very effective to enable multi-level annotation of natural scenes in a large-scale image dataset.