Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Editorial: special issue on learning from imbalanced data sets
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
A study of the behavior of several methods for balancing machine learning training data
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
On the detection of semantic concepts at TRECVID
Proceedings of the 12th annual ACM international conference on Multimedia
Early versus late fusion in semantic video analysis
Proceedings of the 13th annual ACM international conference on Multimedia
To learn representativeness of video frames
Proceedings of the 13th annual ACM international conference on Multimedia
Learning the semantics of multimedia queries and concepts from a small number of examples
Proceedings of the 13th annual ACM international conference on Multimedia
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
Semi-automatic video annotation based on active learning with multiple complementary predictors
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Semantic image classification with hierarchical feature subset selection
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
Dynamic captioning: video accessibility enhancement for hearing impairment
Proceedings of the international conference on Multimedia
Mediapedia: mining web knowledge to construct multimedia encyclopedia
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
In-Image Accessibility Indication
IEEE Transactions on Multimedia
Towards a Relevant and Diverse Search of Social Images
IEEE Transactions on Multimedia
Similarity-based online feature selection in content-based image retrieval
IEEE Transactions on Image Processing
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Large-scale semantic concept detection from large video database suffers from large variations among different semantic concepts as well as their corresponding effective low-level features. In this paper, we propose a novel framework to deal with this obstacle. The proposed framework consists of four major components: feature pool construction, pre-filtering, modeling, and classification. First, a large low-level feature pool is constructed, from which a specific set of features are selected for the latter steps automatically or semi-automatically. Then, to deal with the unbalance problem in training set, a pre-filtering classifier is generated, which the aim of achieving a high recall rate and a certain precision rate nearly 50% for a certain concept. Thereafter, from the pre-filtered training samples, a SVM classifier is built based on the selected features in the feature pool. After that, the SVM classifier is applied to classification of semantic concept. This framework is flexible and extensible in terms of adding new features into the feature pool, introducing human interactions in selecting features, building models for new concepts and adopting active learning.