AN EVALUATION OF DISTINCT FACE RECOGNITION ALGORITHMS USED ON A MOBILE ROBOT When is a algorithm better for face-recognition in motion?
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2023-01-28
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en
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Abstract
As face recognition rose in the 1960s, the art of identifying and recognizing individuals
skyrocketed. A lot of advancements were made such as face features, statistical features
and big data. In video-based facial recognition, a great deal has been accomplished as well.
For example, blurry images can now be changed to sharp images to extract identifiable
faces. However, almost all developments are validated by an accuracy test on a database.
This is why this study aims to experiment with face-recognition algorithms in a dynamic
environment. It will create a quantitative structure to describe the performance of an
algorithm, that not only relies on accuracy. The results clearly show that the superior
algorithm (DLIB) performs worse if the environment is not static and the computational
resources are limited. It also reveals that the perspective of accuracy is not always the
proper approach to evaluate the quality of a face-recognition algorithm.
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Faculteit der Sociale Wetenschappen