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High Scale Fuzzy Video Mining

High Scale Fuzzy Video Mining

Christophe Marsala, Marcin Detyniecki
Copyright: © 2010 |Pages: 14
ISBN13: 9781605668581|ISBN10: 1605668583|ISBN13 Softcover: 9781616924478|EISBN13: 9781605668598
DOI: 10.4018/978-1-60566-858-1.ch015
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MLA

Marsala, Christophe, and Marcin Detyniecki. "High Scale Fuzzy Video Mining." Scalable Fuzzy Algorithms for Data Management and Analysis: Methods and Design, edited by Anne Laurent and Marie-Jeanne Lesot, IGI Global, 2010, pp. 365-378. https://doi.org/10.4018/978-1-60566-858-1.ch015

APA

Marsala, C. & Detyniecki, M. (2010). High Scale Fuzzy Video Mining. In A. Laurent & M. Lesot (Eds.), Scalable Fuzzy Algorithms for Data Management and Analysis: Methods and Design (pp. 365-378). IGI Global. https://doi.org/10.4018/978-1-60566-858-1.ch015

Chicago

Marsala, Christophe, and Marcin Detyniecki. "High Scale Fuzzy Video Mining." In Scalable Fuzzy Algorithms for Data Management and Analysis: Methods and Design, edited by Anne Laurent and Marie-Jeanne Lesot, 365-378. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-60566-858-1.ch015

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Abstract

In this chapter, the authors focus on the use of forests of fuzzy decision trees (FFDT) in a video mining application. They discuss how to learn from a high scale video data sets and how to use the trained FFDTs to detect concepts in a high number of video shots. Moreover, the authors study the effect of the size of the forest on the performance; and of the use of fuzzy logic during the classification process. The experiments are performed on a well-know non-video dataset and on a real TV quality video benchmark.

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