Confidence-based dynamic ensemble for image annotation and semantics discovery
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Concept-oriented video skimming via semantic video classification
Proceedings of the 12th annual ACM international conference on Multimedia
Learning the Semantics of Images by Using Unlabeled Samples
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A probabilistic framework for semantic video indexing, filtering,and retrieval
IEEE Transactions on Multimedia
Concept-oriented indexing of video databases: toward semantic sensitive retrieval and browsing
IEEE Transactions on Image Processing
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Motivated by Google's great success on text document retrieval and recent progresses of semantic video understanding, researchers begin to build new generation of video retrieval systems that are able to support semantic sensitive video retrieval via keywords. Unfortunately, these systems are not able to provide satisfactory results for the masses because of several inter-related challenging problems. We have proposed novel algorithms to resolve some of these problems. Firstly, the salient object based semantic classification algorithm is proposed to extract semantic concepts of video clips. Secondly, the video visualization based interactive retrieval framework is proposed to help users input semantic and visual queries efficiently and effectively. Finally, the concept-oriented skimming algorithm is proposed to help users efficiently check search results.