Abstract
Face recognition is a pattern recognition technique and one of the most important biometrics; it is used in a broad spectrum of applications. Classroom attendance management system is one of the applications. This paper proposes an optimized method of face detection using viola jones and face recognition using SURF and HOG feature extraction methods. The proposed model takes a video frame from an input device, then it detects faces in that frame using proposed optimized face detection method. Lastly, the detected faces are matched with pre-loaded customized database using proposed face recognition method. In addition we have tested our model with other existing model using two different customized datasets. Without human intervention this proposed model almost accurately completes the attendance of students in a class.
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Shafiqul Islam, M., Mahmud, A., Akter Papeya, A., Sultana Onny, I., Uddin, J. (2018). A Combined Feature Extraction Method for Automated Face Recognition in Classroom Environment. In: Thampi, S., Krishnan, S., Corchado Rodriguez, J., Das, S., Wozniak, M., Al-Jumeily, D. (eds) Advances in Signal Processing and Intelligent Recognition Systems. SIRS 2017. Advances in Intelligent Systems and Computing, vol 678. Springer, Cham. https://doi.org/10.1007/978-3-319-67934-1_38
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DOI: https://doi.org/10.1007/978-3-319-67934-1_38
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