In this paper, a demonstrator called BIOFACE incorporating
several facial biometric techniques is described. It includes the
well established Eigenfaces and the recently published Tomofaces
techniques, which perform face recognition based on facial
appearance and dynamics, respectively. Both techniques are
based on the space dimensionality reduction and the enrollment
requires the projection of several positive face samples to the
reduced space. Alternatively, BIOFACE also performs face
recognition based on the matching of Scale Invariant Feature
Transform (SIFT) features.
Moreover, BIOFACE extracts a facial soft biometric profile,
which consists of a bag of facial soft biometric traits such as skin,
hair, and eye color, the presence of glasses, beard and moustache.
The fast and efficient detection of the facial soft biometrics is
performed as a pre-processing step, and employed for pruning the
search for the facial recognition module.
Finally, the demonstrator also detects facial events such as
blinking, yawning and looking-away. The car driver scenario is a
good example to exhibit the importance of such traits to detect
fatigue.
The BIOFACE demonstrator is an attempt to show the potential
and the performance of such facial processing techniques in a
real-life scenario. The demonstrator is built using the C/C++
programming language, which is suitable for implementing image
and video processing techniques due to its fast execution. On top
of that, the Open Source Computer Vision Library (OpenCV),
which is optimized for Intel processors, is used to implement the
image processing algorithms.
