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
Indoor-Outdoor Image Classification
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
CAIVL '97 Proceedings of the 1997 Workshop on Content-Based Access of Image and Video Libraries (CBAIVL '97)
On Image Classification: City vs. Landscape
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Consistent Line Clusters for Building Recognition in CBIR
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
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
On image auto-annotation with latent space models
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Convergence of alternating optimization
Neural, Parallel & Scientific Computations
PLSA-based image auto-annotation: constraining the latent space
Proceedings of the 12th annual ACM international conference on Multimedia
Effective automatic image annotation via a coherent language model and active learning
Proceedings of the 12th annual ACM international conference on Multimedia
Image annotations by combining multiple evidence & wordNet
Proceedings of the 13th annual ACM international conference on Multimedia
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
ICDEW '05 Proceedings of the 21st International Conference on Data Engineering Workshops
Large-Scale Concept Ontology for Multimedia
IEEE MultiMedia
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
ML-KNN: A lazy learning approach to multi-label learning
Pattern Recognition
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Maximum margin clustering made practical
Proceedings of the 24th international conference on Machine learning
Hierarchical classification for automatic image annotation
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Topic segmentation with shared topic detection and alignment of multiple documents
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 6th ACM international conference on Image and video retrieval
Using multiple segmentations for image auto-annotation
Proceedings of the 6th ACM international conference on Image and video retrieval
Correlative multi-label video annotation
Proceedings of the 15th international conference on Multimedia
Dual cross-media relevance model for image annotation
Proceedings of the 15th international conference on Multimedia
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
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Distance metric learning from uncertain side information with application to automated photo tagging
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Multi-label learning by Image-to-Class distance for scene classification and image annotation
Proceedings of the ACM International Conference on Image and Video Retrieval
Image to text translation by multi-label classification
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
Correlated multi-label refinement for semantic noise removal
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
Distance metric learning from uncertain side information for automated photo tagging
ACM Transactions on Intelligent Systems and Technology (TIST)
Mining social images with distance metric learning for automated image tagging
Proceedings of the fourth ACM international conference on Web search and data mining
Neighborhood rough sets based multi-label classification for automatic image annotation
International Journal of Approximate Reasoning
Effective automatic image annotation via integrated discriminative and generative models
Information Sciences: an International Journal
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As the consequence of semantic gap, visual similarity does not guarantee semantic similarity, which in general is conflicting with the inherent assumption of many generative-based image annotation methods. While discriminative learning approach had often been used to classify images into different semantic classes, its efficiency is often impaired by the problems of multi-labeling and large scale concept space typically encountered in practical image annotation tasks. In this paper, we explore solutions to the problems of large scale concept space learning and mismatch between semantic and visual space. To tackle the first problem, we explore the use of higher level semantic space with lower dimension by clustering correlated keywords into topics in the local neighborhood. The topics are used as lexis for assigning multiple labels for unlabeled images. To tackle the problem of semantic gap, we aim to reduce the bias between visual and semantic spaces by finding optimal margins in both spaces. In particular, we propose an iterative solution by alternately maximizing the sum of the margins to reduce the gap between visual similarity and semantic similarity. The experimental results on the ECCV2002 benchmark show that our method outperforms the state-of-the-art generative-based annotation method MBRM and discriminative-based ASVM-MIL by 9% and 11% in terms of F1 measure respectively.