A Temporal Encoder-Decoder Approach to Extracting Blood Volume Pulse Signal Morphology from Face Videos

Fulan Li, Surendrabikram Thapa, Shreyas Bhat, Abhijit Sarkar, A. Lynn Abbott

Abstract:

This paper considers methods for extracting blood
volume pulse (BVP) representations from video of the
human face. Whereas most previous systems have been
concerned with estimating vital signs such as average heart
rate, this paper addresses the more difficult problem of
recovering BVP signal morphology. We present a new
approach that is inspired by temporal encoder-decoder
architectures that have been used for audio signal separation.
As input, this system accepts a temporal sequence
of RGB (red, green, blue) values that have been spatially
averaged over a small portion of the face. The output
of the system is a temporal sequence that approximates
a BVP signal. In order to reduce noise in the recovered
signal, a separate processing step extracts individual pulses
and performs normalization and outlier removal. After
these steps, individual pulse shapes have been extracted
that are sufficiently distinct to support biometric authentication.
Our findings demonstrate the effectiveness of
our approach in extracting BVP signal morphology from
facial videos, which presents exciting opportunities for
further research in this area.