What image information is important in silhouette-based gait recognition?
Published 13 November 2004
Galina Veres, Layla Gordon, J.N. Carter, Mark Nixon
Citations147
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TL;DR
This paper aims to investigate the important features in silhouette-based gait recognition from point of view of statistical analysis and shows that the average silhouette includes a static component of gait (head and body) as the most important image part, while dynamic component ofgait (swings of legs and arms) is ignored as the least important information.
Abstract
Gait recognition has recently gained significant attention, especially in vision-based automated human identification at a distance in visual surveillance and monitoring applications. Silhouette-based gait recognition is one of the most popular methods for recognising moving shapes. This paper aims to investigate the important features in silhouette-based gait recognition from point of view of statistical analysis. It is shown that the average silhouette includes a static component of gait (head and body) as the most important image part, while dynamic component of gait (swings of legs and arms) is ignored as the least important information. At the same time ignoring dynamic part of gait can result in loss in recognition rate in some cases, and the importance of better motion estimation is underlined.
Keywords
Computer ScienceEngineering
BiometricsApplied Multivariate Statistical Analysis.
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