Silhouette analysis-based gait recognition for human identification
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Abstract
Human identification at a distance has recently gained growing interest from computer vision researchers. Gait recognition aims essentially to address this problem by identifying people based on the way they walk. In this paper, a simple but efficient gait recognition algorithm using spatial-temporal silhouette analysis is proposed. For each image sequence, a background subtraction algorithm and a simple correspondence procedure are first used to segment and track the moving silhouettes of a walking figure. Then, eigenspace transformation based on principal component analysis (PCA) is applied to time-varying distance signals derived from a sequence of silhouette images to reduce the dimensionality of the input…
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4Topics & keywords
Topics
Keywords
- Silhouette
- Artificial intelligence
- Pattern recognition (psychology)
- Background subtraction
- Principal component analysis
- Computer science
- Computer vision
- Gait
UN Sustainable Development Goals
- Sustainable cities and communities
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