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• W1549460003 abstract "Different biometric traits such as face appearance and heartbeat signal from Electrocardiogram (ECG)/Phonocardiogram (PCG) are widely used in the human identity recognition. Recent advances in facial video based measurement of cardio-physiological parameters such as heartbeat rate, respiratory rate, and blood volume pressure provide the possibility of extracting heartbeat signal from facial video instead of using obtrusive ECG or PCG sensors in the body. This paper proposes the Heartbeat Signal from Facial Video (HSFV) as a new biometric trait for human identity recognition, for the first time to the best of our knowledge. Feature extraction from the HSFV is accomplished by employing Radon transform on a waterfall model of the replicated HSFV. The pairwise Minkowski distances are obtained from the Radon image as the features. The authentication is accomplished by a decision tree based supervised approach. The potential of the proposed HSFV biometric for human identification is demonstrated on a public database." @default.
• W1549460003 created "2016-06-24" @default.
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• W1549460003 date "2015-01-01" @default.
• W1549460003 modified "2023-09-24" @default.
• W1549460003 title "Heartbeat Signal from Facial Video for Biometric Recognition" @default.
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• W1549460003 doi "https://doi.org/10.1007/978-3-319-19665-7_14" @default.
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