[1]LI Yibo,LI Kun.Gait recognition based on dual view and multiple feature information fusion[J].CAAI Transactions on Intelligent Systems,2013,8(1):74-79.[doi:10.3969/j.issn.1673-4785.201209033]
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Gait recognition based on dual view and multiple feature information fusion

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 8 Number of periods: 2013 1 Page number: 74-79 Column: 学术论文—机器感知与模式识别 Public date: 2013-03-25
Title:
Gait recognition based on dual view and multiple feature information fusion
Author(s):
LI Yibo;  LI Kun
College of Automation, Shenyang Aerospace University, Shenyang 110136, China
Keywords:
gait recognition;  multiple feature information fusion;  dual view;  Procrustes mean shape;  active energy image;  two dimensional partial preserving projections
CLC:
TP391.41
DOI:
10.3969/j.issn.1673-4785.201209033
Abstract:
In view of low recognition rate of single view and complexity of multi view algorithm, a research was conducted examining the gait recognition under dual view. Current research on the contour characteristic of the human body in frontal view and the dynamic characteristics of human walking in side view was examined using the complementary features of the gait information under multi view. Also the gait sequences were obtained utilizing the two views respectively, and then preprocessed to obtain simply connected body silhouettes. Next, the Procrustes mean shape was extracted from the front view, and the active energy images (AEI) was calculated by side view. However, each of the AEI was projected to a low dimensional feature subspace via two dimensional local preserving projections (2D LPP). The final recognition result was obtained by fusing recognition results of two perspectives. The experiments in CASIA dataset(Dataset B) obtained a high recognition rate and achieved the expected effect of recognition.
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