Multimodal person search combining information fusion and relevance feedback
| Autor: | Amjad Samour, Touradj Ebrahimi, Lutz Goldmann, Thomas Sikora |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
relevance feedback
Class (computer programming) Information retrieval Exploit Computer science content based multimedia retrieval multimodal fusion Relevance feedback Sensor fusion sensing people Visualization Support vector machine Search engine Query by Example computer computer.programming_language |
| Zdroj: | MMSP |
| DOI: | 10.1109/mmsp.2009.5293272 |
| Popis: | With the increasing amount of multimedia data, efficient tools for search and retrieval are needed. Since people are naturally one of the most interesting objects within these documents, a system for multimodal person search and retrieval has been developed. It combines the audiovisual analysis of persons with the query by example paradigm and relevance feedback to provide an efficient tool for searching multimedia data. For the relevance feedback, one and two class approaches are considered and compared to each other. Multimodal fusion techniques are used to exploit the complementary character of the audio and video information. The experimental results prove that multimodal person search and retrieval is feasible and more efficient than manual exploration. |
| Databáze: | OpenAIRE |
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