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A new view-invariant feature for cross-view gait recognition

Date

Authors

Kusakunniran, Worapan

Wu, Qiang

Zhang, Jian

Ma, Yi

Li, Hongdong

Publisher

Institute of Electrical and Electronics Engineers (IEEE Inc)

Abstract

Human gait is an important biometric feature which is able to identify a person remotely. However, change of view causes significant difficulties for recognizing gaits. This paper proposes a new framework to construct a new view-invariant feature for cros

Keywords

Keywords: Gait recognition; Human identification; Low-rank textures; Procrustes shape analysis; Sparse errors; View invariants; Biometrics; Textures; Gait analysis Gait recognition; gross sparse error; human identification; low-rank texture; procrustes shape analysis; view invariant

URI

http://hdl.handle.net/1885/74872

Collections

ANU Research Publications

Source

IEEE Transactions on Information Forensics and Security

Type

Journal article

DOI

10.1109/TIFS.2013.2252342

Restricted until

2037-12-31

Downloads

File

Description

01_Kusakunniran_A_new_view-invariant_feature_2013.pdf (1.53 MB)