In the last decades there has been such a fundamental development in the technologies including technologies focusing on face detection and identification supported by computer vision. Algorithm optimization has reached the point, when face detection is possible on mobile devices. At the outset, this work analy-ses common used algorithms for face detection and identification, for instance Haar features, LBP, EigenFaces and FisherFaces. Moreover, this work focuses on more up-to-date approaches of this topic, such as convolutional neural networks, or FaceNet from Google. The goal of this work is a design and its subsequent im-plementation of an automated, monitoring system designated for a lab, which is based on aforementioned algorithms. Within the design of the monitoring system, algorithms are compared with each other and their success rate and possible ap-plication in the final solution is evaluated.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:429794 |
| Date | January 2019 |
| Creators | Gvizd, Peter |
| Source Sets | Czech ETDs |
| Language | Slovak |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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