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2020 | OriginalPaper | Buchkapitel

Face Recognition Using DELF Feature Descriptors on RGB-D Data

verfasst von : Andrey Kuznetsov

Erschienen in: Analysis of Images, Social Networks and Texts

Verlag: Springer International Publishing

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Abstract

Face recognition is a very challenging and important task in many areas. This sort of algorithms is used in security systems, for person authorization tasks, person reidentification, etc. In face recognition speed and quality are very important, but in this research, we concentrate on quality improvement. In this paper we propose a new solution for face recognition using RGB-D data obtained with Kinect sensor. The proposed solution is based on a new type of feature descriptors – Deep Learning Features (DELF), which showed high classification results on Google landmarks dataset. We compared DELF descriptors with HOG, MSER and SURF descriptors using two classification schemes: error correcting output codes (ECOC) and decision trees. Conducted experiments showed an improvement in classification quality using F1 score metric when face recognition is based on DELF descriptors and ECOC classifier.

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Metadaten
Titel
Face Recognition Using DELF Feature Descriptors on RGB-D Data
verfasst von
Andrey Kuznetsov
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-39575-9_24