Key frame based Face in Video Recognition using Multi-Artificial Neural Network

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DR. S. WILSON

Abstract

Face in video recognition has several challenges. Although deep learning approaches have
achieved performance that surpasses people for still image- face recognition, video- face recognition
remains a challenging task due to the large volume of data to be processed and intra / intervideo
variations in pose, lighting, occlusion, scene, blur, video quality, etc. In this paper, deep convolutional
neural network is used for feature extraction and artificial neural network is used for face recognition.
The computation overhead of these deep learning approaches is reduced by introducing keyframe
based face recognition in video. The low-quality frames are removed by extracting keyframes. The
proposed method is tested on YTF dataset and the results are compared with recent methods. The
experimental results substantially proved that the proposed method achieves a higher accuracy rate of
98.36% when compared with other recent methods.

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How to Cite
DR. S. WILSON. (2022). Key frame based Face in Video Recognition using Multi-Artificial Neural Network. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 10(3), 970–979. https://doi.org/10.17762/turcomat.v10i3.12050
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