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Gait recognition using linear time normalization
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DOI：10.1016/j.patcog.2005.10.013.png)
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摘要
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We present a novel system for gait recognition. Identity recognition and verification are based on the matching of linearly time-normalized gait walking cycles. A novel feature extraction process is also proposed for the transformation of human silhouettes into low-dimensional feature vectors consisting of average pixel distances from the center of the silhouette. By using the best-performing of the proposed methodologies, improvements of 8-20% in recognition and verification performance are seen in comparison to other known methodologies on the Gait Challenge database. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Keyword:
gait
angular analysis
time normalization
recognition
verification
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IF:
7.6
论文数:
1.3W
被引数:
4.5W
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