The vocabulary problem in human-system communication
Communications of the ACM
The físchlár digital video system: a digital library of broadcast TV programmes
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 13th annual ACM international conference on Multimedia
Large-Scale Concept Ontology for Multimedia
IEEE MultiMedia
Extreme video retrieval: joint maximization of human and computer performance
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
A review of text and image retrieval approaches for broadcast news video
Information Retrieval
Interactive image search by 2D semantic map
Proceedings of the 19th international conference on World wide web
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Botanical data retrieval system supporting discovery learning
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Extending information unit across media streams for improving retrieval effectiveness
Data & Knowledge Engineering
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We propose a new interactive image and video retrieval system called multi-query interactive retrieval, which is designed to jointly optimize the retrieval performance on multiple query topics. The proposed system employs a learning-based hybrid retrieval approach, which can automatically switch between tagging and browsing interface based on user labeling efficiency. To formalize the retrieval process, we use two formal annotation models to track and estimate the retrieval time for each method. Based on the parameters of these models, the system integrates the tagging-based and browsing-based methods in order to minimize overall retrieval time across the full set of query topics. This hybrid multi-topic retrieval approach is demonstrated to be highly effective on two large-scale video collections.