Analysis gait recognition performance based on the walking speed
This report proposes the gait recognition algorithm based on principal component analysis (PCA) for gait energy image (GEI) and analysts the impact of various walking speeds on the gait recognition. The gait energy image is obtained by preprocessing the original gait sequence. The eigenvalues and...
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sg-ntu-dr.10356-751932023-07-07T17:58:05Z Analysis gait recognition performance based on the walking speed Liu, Mengrui Ma Kai Kuang School of Electrical and Electronic Engineering DRNTU::Engineering This report proposes the gait recognition algorithm based on principal component analysis (PCA) for gait energy image (GEI) and analysts the impact of various walking speeds on the gait recognition. The gait energy image is obtained by preprocessing the original gait sequence. The eigenvalues and the corresponding eigenvectors are extracted by the principal component analysis. After the principal components are obtained, they are projected to the low dimension space and classified using the k-nearest neighbor method. The algorithm is verified on the CASIA database. The experimental results show that the recognition performance can be effected by other factors except existing well-known factors. Bachelor of Engineering 2018-05-30T02:21:32Z 2018-05-30T02:21:32Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75193 en Nanyang Technological University 60 p. application/pdf |
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DRNTU::Engineering Liu, Mengrui Analysis gait recognition performance based on the walking speed |
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This report proposes the gait recognition algorithm based on principal component analysis (PCA) for gait energy image (GEI) and analysts the impact of various walking speeds on the gait recognition. The gait energy image is obtained by preprocessing the original gait sequence. The eigenvalues and the corresponding eigenvectors are extracted by the principal component analysis. After the principal components are obtained, they are projected to the low dimension space and classified using the k-nearest neighbor method. The algorithm is verified on the CASIA database. The experimental results show that the recognition performance can be effected by other factors except existing well-known factors. |
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Ma Kai Kuang |
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Ma Kai Kuang Liu, Mengrui |
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Final Year Project |
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Liu, Mengrui |
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Liu, Mengrui |
title |
Analysis gait recognition performance based on the walking speed |
title_short |
Analysis gait recognition performance based on the walking speed |
title_full |
Analysis gait recognition performance based on the walking speed |
title_fullStr |
Analysis gait recognition performance based on the walking speed |
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Analysis gait recognition performance based on the walking speed |
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analysis gait recognition performance based on the walking speed |
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2018 |
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http://hdl.handle.net/10356/75193 |
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1772828359867236352 |