Dynamic Texture Based Gait Recognition

被引：0

作者：

Kellokumpu, Vili ^{[1
]}

Zhao, Guoying ^{[1
]}

Li, Stan Z. ^{[2
]}

Pietikainen, Matti ^{[1
]}

机构：

[1] Univ Oulu, Machine Vis Grp, POB 4500, Oulu, Finland

[2] Chinese Acad Sci, Inst Automat, Ctr Biometr & Secur Res, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China

来源：

ADVANCES IN BIOMETRICS | 2009年 / 5558卷

基金：

芬兰科学院;

关键词：

Gait recognition; LBP-TOP; multiresolution LBP; uniform patterns;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a novel approach for human gait recognition that inherently combines appearance and motion. Dynamic texture descriptors, Local Binary Patterns from Three Orthogonal Planes (LBP-TOP), are used to describe human gait in a spatiotemporal way. We also propose a new coding of multire-solution uniform Local Binary Patterns and use it in the construction of spatiotemporal LBP histograms. We show the suitability of the representation for gait recognition and test our method on a Popular CMU MoBo dataset. We then compare our result to the state of the art methods.

引用

页码：1000 / +

页数：3

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