Heartbeat Signal from Facial Video for Biometric Recognition

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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.
Original languageEnglish
Title of host publicationImage Analysis : 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings
Number of pages12
PublisherSpringer
Publication date2015
Pages165-174
ISBN (Print)978-3-319-19664-0
ISBN (Electronic)978-3-319-19665-7
DOIs
Publication statusPublished - 2015
EventScandinavian Conference on Image Analysis - Copenhagen, Denmark
Duration: 15 Jun 201517 Jun 2015
Conference number: 19

Conference

ConferenceScandinavian Conference on Image Analysis
Number19
CountryDenmark
CityCopenhagen
Period15/06/201517/06/2015
SeriesLecture Notes in Computer Science
Volume9127
ISSN0302-9743

Fingerprint

Biometrics
Radon
Electrocardiography
Decision trees
Authentication
Feature extraction
Blood
Sensors

Keywords

  • biometric
  • identification
  • Radon transform
  • heartbeat
  • facial video

Cite this

Haque, M. A., Nasrollahi, K., & Moeslund, T. B. (2015). Heartbeat Signal from Facial Video for Biometric Recognition. In Image Analysis: 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings (pp. 165-174). Springer. Lecture Notes in Computer Science, Vol.. 9127 https://doi.org/10.1007/978-3-319-19665-7_14
Haque, Mohammad Ahsanul ; Nasrollahi, Kamal ; Moeslund, Thomas B. / Heartbeat Signal from Facial Video for Biometric Recognition. Image Analysis: 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings. Springer, 2015. pp. 165-174 (Lecture Notes in Computer Science, Vol. 9127).
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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.",
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Haque, MA, Nasrollahi, K & Moeslund, TB 2015, Heartbeat Signal from Facial Video for Biometric Recognition. in Image Analysis: 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings. Springer, Lecture Notes in Computer Science, vol. 9127, pp. 165-174, Scandinavian Conference on Image Analysis, Copenhagen, Denmark, 15/06/2015. https://doi.org/10.1007/978-3-319-19665-7_14

Heartbeat Signal from Facial Video for Biometric Recognition. / Haque, Mohammad Ahsanul; Nasrollahi, Kamal; Moeslund, Thomas B.

Image Analysis: 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings. Springer, 2015. p. 165-174 (Lecture Notes in Computer Science, Vol. 9127).

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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AB - 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.

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Haque MA, Nasrollahi K, Moeslund TB. Heartbeat Signal from Facial Video for Biometric Recognition. In Image Analysis: 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings. Springer. 2015. p. 165-174. (Lecture Notes in Computer Science, Vol. 9127). https://doi.org/10.1007/978-3-319-19665-7_14