Original Contribution: Stacked generalization
Neural Networks
The LIMSI Broadcast News transcription system
Speech Communication - Special issue on automatic transcription of broadcast news data
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Fusion of Global and Local Information for Object Detection
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Discriminative model fusion for semantic concept detection and annotation in video
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
Combining Local and Global Image Features for Object Class Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Early versus late fusion in semantic video analysis
Proceedings of the 13th annual ACM international conference on Multimedia
Early versus late fusion in semantic video analysis
Proceedings of the 13th annual ACM international conference on Multimedia
On supervision and statistical learning for semantic multimedia analysis
Journal of Visual Communication and Image Representation
Video shot classification using lexical context
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Image and video indexing using networks of operators
Journal on Image and Video Processing
Image and video indexing using networks of operators
Journal on Image and Video Processing
Classifier fusion for SVM-based multimedia semantic indexing
ECIR'07 Proceedings of the 29th European conference on IR research
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Automatic semantic classification of video databases is very useful for users searching and browsing but it is a very challenging research problem as well. Combination of visual and text modalities is one of the key issues to bridge the semantic gap between signal and semantic. In this paper, we propose to enhance the classification of high-level concepts using intermediate topic concepts and study various fusion strategies to combine topic concepts with visual features in order to outperform unimodal classifiers. We have conducted several experiments on the TRECVID'05 collection and show here that several intermediate topic classifiers can bridge parts of the semantic gap and help to detect high-level concepts.