论文信息 - The mediamill large.lexicon concept suggestion engine

The mediamill large.lexicon concept suggestion engine

In this technical demonstration we show the current version of the MediaMill system, a search engine that facilitates access to news video archives at a semantic level. The core of the system is a lexicon of 436 automatically detected semantic concepts. To handle such a large lexicon in retrieval, an engine is developed which automatically selects a set of relevant concepts based on the textual query and example images. The result set can be browsed easily to obtain the final result for the query.

[1] Alan F. Smeaton,et al. Large Scale Evaluations of Multimedia Information Retrieval: The TRECVid Experience , 2005, CIVR.

[2] Cor J. Veenman,et al. Robust Scene Categorization by Learning Image Statistics in Context , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[3] Alexander G. Hauptmann,et al. LSCOM Lexicon Definitions and Annotations (Version 1.0) , 2006 .

[4] Philip Resnik,et al. Using Information Content to Evaluate Semantic Similarity in a Taxonomy , 1995, IJCAI.

[5] Marcel Worring,et al. MediaMill: exploring news video archives based on learned semantics , 2005, MULTIMEDIA '05.

[6] George A. Miller,et al. WordNet: A Lexical Database for English , 1995, HLT.

[7] Marcel Worring,et al. The Semantic Pathfinder: Using an Authoring Metaphor for Generic Multimedia Indexing , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.