HUMAN ACTION CLASSIFICATION USING SURF BASED SPATIO-TEMPORAL CORRELATED DESCRIPTORS

被引：0

作者：

Sabri, A. Q. Md ^{[1
]}

Boonaert, J. ^{[1
]}

Lecoeuche, S. ^{[1
]}

Mouaddib, E. ^{[2
]}

机构：

[1] Ecole Mines Douai, Informat & Automat Res Unit, Douai, France

[2] Univ Picardie Jules Verne, MIS Lab, Amiens, France

来源：

2012 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2012) | 2012年

关键词：

SURF; correlations; human action; classification;

D O I：

暂无

中图分类号：

TB8 [摄影技术];

学科分类号：

0804 ;

摘要：

This paper proposes a method for human action classification by utilizing correlations between SURF based descriptors. This approach provides us a novel type of descriptor that can be used for action classification. The method proposed is tested using an SVM classification technique. For evaluation purposes, the KTH action recognition dataset, which is a standard benchmark for this area is used as it is one of the most well known and challenging dataset. The method proposed was able to successfully classify different action classes.

引用

页码：1401 / 1404

页数：4

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