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Erschienen in:
A Quantitative Assessment of Image Normalization for Classifying Histopathological Tissue of the Kidney Kapitel lesen Erstes Kapitel lesen

2017 | Supplement | Buchkapitel

On the Diffusion Process for Heart Rate Estimation from Face Videos Under Realistic Conditions

verfasst von : Christian S. Pilz, Jarek Krajewski, Vladimir Blazek

Erschienen in: Pattern Recognition

Verlag: Springer International Publishing

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Abstract

This work addresses the problem of estimating heart rate from face videos under real conditions using a model based on the recursive inference problem that leverages the local invariance of the heart rate. The proposed solution is based on the canonical state space representation of an Itō process and a Wiener velocity model. Empirical results yield to excellent real-time and estimation performance of heart rate in presence of disturbing factors, like rigid head motion, talking and facial expressions under natural illumination conditions making the process of heart rate estimation from face videos applicable in a much broader sense. To facilitate comparisons and to support research we made the code and data for reproducing the results public available.

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Vorheriges Kapitel Optical Flow-Based 3D Human Motion Estimation from Monocular Video
Nächstes Kapitel Multi-view Continuous Structured Light Scanning
Fußnoten
1
We also reimplemented other methods [14, 25, 41], since their code is not available. Unfortunately, we obtained worse results.
 
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Metadaten
Titel
On the Diffusion Process for Heart Rate Estimation from Face Videos Under Realistic Conditions
verfasst von
Christian S. Pilz
Jarek Krajewski
Vladimir Blazek
Copyright-Jahr
2017
Buch
Pattern Recognition

Print ISBN: 978-3-319-66708-9

Electronic ISBN: 978-3-319-66709-6

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-66709-6_29

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