An Effective Facial Image Verification Based Attendance Management System
| Autor: | Zhan-Li Sun, Zeng-Mei Li, Hui-Na Dai, Xia Chen |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
business.industry Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology 01 natural sciences Facial recognition system Image (mathematics) Attendance management system Core (graph theory) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence Face detection business 010606 plant biology & botany |
| Zdroj: | Advances in Neural Networks – ISNN 2018 ISBN: 9783319925363 ISNN |
| DOI: | 10.1007/978-3-319-92537-0_73 |
| Popis: | In this paper, we present an effective facial image verification based automated attendance management system (FIV-AMS). The proposed system can be divided into three main components: face detection, image pre-processing, and face recognition. The core step of our attendance management system is the Gist feature extraction based face recognition, which can achieve three functions. Experimental results demonstrate the validity and feasibility of the proposed system by using the statical model and the dynamic model. |
| Databáze: | OpenAIRE |
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