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Vocabulary-Supported Image Retrieval

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84284

Vogel,  J
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Schiele, B., & Vogel, J. (2000). Vocabulary-Supported Image Retrieval. 1st DELOS Workshop on Information Seeking, Searching and Querying in Digital Libraries, Zurich, Switzerland.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-E3EA-0
Zusammenfassung
Today's content-based image retrieval systems (CBIR) mostly rely on a predefined set of low-level image features and incorporate user-interactions using techniques such as relevance feedback. These systems however do not take advantage of the fact that in many applications queries can be formulated using a vocabulary. In this paper we propose a general framework which allows to use vocabulary at several levels. The framework should be seen as an extension of today's CBIR systems enabling the use of vocabulary as well as online learning techniques such as relevance feedback. The image detectors supporting the vocabulary can be either implemented directly or learned offline from examples and user-interactions.