DocumentCode :
1564374
Title :
Discovering knowledge for better video indexing based on colors
Author :
Detyniecki, Marcin ; Marsala, Christophe
Author_Institution :
CNRS, Univ. Pierre et Marie Curie, Paris, France
Volume :
2
fYear :
2003
Firstpage :
1177
Abstract :
In this paper, we present the discovery of rules for different challenges encountered in video indexing. These rules should be considered as knowledge that can be used as a guideline for the development of better indexing tools. We use a fuzzy decision tree to extract the rules based on color proportions of key-frames extracted from one single video-news. Experimental results and comparisons with other data mining tools are presented.
Keywords :
data mining; database indexing; decision trees; fuzzy set theory; image colour analysis; knowledge based systems; multimedia databases; video coding; video databases; color based video indexing; data mining tools; fuzzy decision tree; key-frames color proportions; video news; Application software; Automation; Data mining; Decision trees; Guidelines; Humans; Indexing; Navigation; Time factors; Video sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN :
0-7803-7810-5
Type :
conf
DOI :
10.1109/FUZZ.2003.1206598
Filename :
1206598
Link To Document :
بازگشت