Video retrieval by feature learning in key frames

被引：0
|
作者：
Pickering, MJ
Rüger, SM
Sinclair, D
机构：
[1] Univ London Imperial Coll Sci Technol & Med, Dept Comp Technol & Med, London SW7 2BZ, England
[2] AT&T Labs Cambridge, Cambridge CB2 1QA, England
来源：
IMAGE AND VIDEO RETRIEVAL | 2002年 / 2383卷
关键词：
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
We evaluate the application of feature-vector based image retrieval methods to the problem of video retrieval. A vast number of primitive features is. calculated for each of the key frames generated by a segmentation process, and we examine the use of three methods for retrieving video segments using the features - a vector space model, a learning method using the AdaBoost algorithm, and a k-nearest neighbour approach.
引用
收藏
页码：309 / 317
页数：9
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