Gait recognition using linear time normalization
نویسندگان
چکیده
We present a novel system for gait recognition. Identity recognition and verification are based on the matching of linearly timenormalized 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. 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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عنوان ژورنال:
- Pattern Recognition
دوره 39 شماره
صفحات -
تاریخ انتشار 2006