High Scale Fuzzy Video Mining

C. Marsala, Marcin Detyniecki
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引用次数: 4

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.
大规模模糊视频挖掘
在本章中,作者重点讨论了模糊决策树森林(FFDT)在视频挖掘中的应用。他们讨论了如何从高规模的视频数据集中学习,以及如何使用训练有素的ffdt来检测大量视频镜头中的概念。此外,作者还研究了森林规模对绩效的影响;以及模糊逻辑在分类过程中的应用。实验在一个知名的非视频数据集和一个真实的电视质量视频基准上进行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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