Detecting live person for the face recognition problem : submitted in partial fulfilment of the requirements for the degree of Master of Information Sciences, Massey University
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Date
2016
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Massey University
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Abstract
Face recognition has been a challenging problem for computer
vision scientists for the last few decades. Hence it was the center of
attention for computer vision researchers. The purpose of this research
is to improve the security of the face recognition system by identifying
the liveness of a person in front of a camera to be recognised.
The objective was to detect if the images used to be recognised
reflect a real person’s face, i.e., a live person’s face instead of just a
static image of the face. This can be achieved by randomly asking the
person to carry out certain tasks. Simple tasks such as blinking an eye
or smiling can then be repeated randomly according to the instructions
given by the new system, so even a video of the target face made
previously would not be able to perform the authentication easily.
Each component of the system were tested separately. The accuracy
of the face detection component was impressively at 98.93%. The eye
blinking detection uses a new proposed method with a high accuracy of
91%. Face recognition component was also tested and had a high
recognition rate of 96%.
Keywords: Face Recognition, Face Detection, Eigenfaces, OpenCV,
Face Anti-Spoofing, Eye Detection, Smile Detection, Eye Blinking
Detection
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Human face recognition, Computer vision, Face perception, Computer science, Face detection, Eigenfaces, OpenCV, Face anti-spoofing, Eye detection, Smile detection, Eye blinking detection, Research Subject Categories::TECHNOLOGY::Information technology::Image analysis