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Paralel Spatial Pyramid Convolutional Neural Network untuk Verifikasi Kekerabatan berbasis Citra Wajah

Reza Fuad Rachmadi, I Ketut Eddy Purnama
Published: 31 October 2018
Jurnal Teknologi dan Sistem Komputer , Volume 6, pp 152-157; doi:10.14710/jtsiskom.6.4.2018.152-157

Abstract: In this paper, we proposed a parallel spatial pyramid CNN classifier for image-based kinship verification problem. Two face images that compared for kinship verification treated as input for each parallel convolutional network of our classifier. Each parallel convolutional network constructed using spatial pyramid CNN classifier. At the end of the convolutional network, we use three fully connected layers to combine each spatial pyramid CNN features and decided the final kinship prediction. We tested the proposed classifier using large-scale kinship verification dataset, called FIW dataset, consists of seven kinship problems from 1,000 families. In our approach, we treated each kinship problem as a binary classification problem with two output. We train our classifier separately for each kinship problem with same training configuration. Overall, our proposed method can achieve an average accuracy of more than 60% and outperform the baseline method.
Keywords: neural / verification / classifier / parallel / training / CNN / kinship / convolutional / Spatial Pyramid

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