Gait Recognition Based on PCA and LDA
نویسندگان
چکیده
This paper proposes a new gait recognition method using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is first applied to 1D time-varying distance signals derived from a sequence of silhouette images to reduce it’s dimensionality. Then, LDA is performed to optimize the pattern class ificovtion..And,Spatiotemporal Correlation (STC) and Normalized Euclidean Distance (NED) are respectively used to measur the two different sequences and K nearest neighbor classification (KNN) are finally performed for recognition. The experimental results show the PCA and LDA based gait recognition algorithm is better than that based on PCA.
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