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- W2288016908 abstract "Multimodal biometric has ability to improve the performance in biometric recognition system. In this paper we are using face biometrics to improve the performance of gait biometric. Here proposed multimodal biometrics use feature level fusion strategy. Here walking person face and gait data are captured in the form of image, and combination of this face and gait images PCA feature represent as combined feature vector. Principal component analysis algorithm is used to reduce the dimensionality of this PCA feature vector. At the testing phase we give the similar input vector which is the combination of both face and gait. Our experiments show that when we are using only gait feature of individual then its recognition rate is 67%. But when we combined gait with face then gait performance can be improved up to 90%.This system can be used in communities where automated method is require to determine the identity of individual." @default.
- W2288016908 created "2016-06-24" @default.
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- W2288016908 date "2011-01-01" @default.
- W2288016908 modified "2023-09-28" @default.
- W2288016908 title "Fusion of Gait and Facial Feature Using PCA" @default.
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- W2288016908 doi "https://doi.org/10.1007/978-3-642-27183-0_42" @default.
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