Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient use of local edge histogram descriptor
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
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
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
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
AnnoSearch: Image Auto-Annotation by Search
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Correlated Label Propagation with Application to Multi-label Learning
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Image annotation by large-scale content-based image retrieval
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bipartite graph reinforcement model for web image annotation
Proceedings of the 15th international conference on Multimedia
Automatic image annotation using visual content and folksonomies
Multimedia Tools and Applications
Expert Systems with Applications: An International Journal
NUS-WIDE: a real-world web image database from National University of Singapore
Proceedings of the ACM International Conference on Image and Video Retrieval
Baselines for Image Annotation
International Journal of Computer Vision
A feature-word-topic model for image annotation
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Visual object-action recognition: Inferring object affordances from human demonstration
Computer Vision and Image Understanding
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
Ontology modularization to improve semantic medical image annotation
Journal of Biomedical Informatics
Image annotation by composite kernel learning with group structure
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Personalizing automated image annotation using cross-entropy
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Invariant object recognition and pose estimation with slow feature analysis
Neural Computation
Image annotation using bi-relational graph of images and semantic labels
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Segmentation by Fusion of Histogram-Based -Means Clusters in Different Color Spaces
IEEE Transactions on Image Processing
Content-based annotation and classification framework: a general multi-purpose approach
Proceedings of the 17th International Database Engineering & Applications Symposium
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Automatic image annotation is a challenging problem in pattern recognition. Large annotation databases are difficult to build, and the existing models can only label small scale of image sets. In order to solve the problems with the annotation of large databases, a web community based image annotation model is proposed. Firstly, an algorithm for effectively selecting training image is proposed to delete noise images from training dataset. Secondly, a method based on weighted KNN is proposed to assign weights on each image in nearest neighbor collections, which taking into account the impacts of different images in nearest neighbor collections. By this way, training images that are more similar to unlabeled image will have higher confidences in the annotation propagation process. Thirdly, an annotation refinement method based on WordNet level is proposed to improve the annotation results of non-abstract words. Our model is appropriate for annotating images from large-scale real web community. Experiments conducted on large-scale datasets verify the effectiveness of the proposed model.