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Body Mass Index Prediction and Classification Based on Facial Morphological Cues Using Multinomial Logistic Regression

Venkata Rao Maddumala, ArunKumar R
Revue d'Intelligence Artificielle , Volume 35, pp 105-113; doi:10.18280/ria.350201

Abstract: This paper presents a novel method for body mass index prediction and classification based on the multinomial logistic regression model. The facial geometrical features are extracted and the logistic regression model parameters estimated based on the features. Based on the model parameters, the logistic model is fit in to predict the body mass index and classifies. Two different facial datasets are taken into account for the experiments. Each dataset is divided into two sets. One set is used to estimate the parameters while the other is used to fit-in the model and predicts the body mass index and classifies itself. The obtained outcome results show that the performance of the proposed method is comparable to the state-of-the-art techniques.
Keywords: model / facial / Classification / body mass index prediction / fit / multinomial logistic

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