Evaluation campaigns and TRECVid
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Image and video indexing using networks of operators
Journal on Image and Video Processing
Foundations and Trends in Information Retrieval
Video corpus annotation using active learning
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
CoVidA: pen-based collaborative video annotation
Proceedings of the 1st International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications
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The LIGVID system is designed for online interactive video shots retrieval and annotation. It uses a user-controlled combination of multiple criteria: keywords, phonetic string, similarity to example images, semantic categories, and relevance feedback strategies: visual and temporal similarity to already identified positive images. In addition to Relevance Feedback processes, the system runs in background an active learning algorithm to better model the user's information need. Previous participation to video retrieval challenges has permit to show the effectiveness of our system.