Age Estimation of Person Based on Face Features

S. Hatture, Ashwini Gouripur
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Abstract

In the era of information technology the social media and other sources of evidence are usually used to spot suspects and victims of crimes by police. Investigators generally use individual characteristics like gender, age, weight, height, etc. from unknown speculate to testimony in their perception. For example in child abuse investigations victim age is essential in the detection of the offenses' classification. Machine learning methods are used in the analysis of digital photographs to identify soft biometric. Investigator benefits from this to improve their cases. This paper presents an efficient intelligent system for age estimation of a person's by employing the facial features. The facial information employing the deep learning technique that is transfer learning based on Convolutional Neural Networks will estimate the age of the person. The method contains pre-trained model, convolutional base, and classifier. The proposed method is efficient and outer performs the state-of-the-art techniques.
基于人脸特征的人年龄估计
在信息技术时代,社交媒体和其他证据来源通常被警察用来发现犯罪嫌疑人和受害者。调查人员通常使用个人特征,如性别、年龄、体重、身高等,从未知的推测到他们感知的证词。例如,在虐待儿童的调查中,受害人的年龄对于判定罪行的分类至关重要。机器学习方法用于分析数字照片以识别软生物特征。调查员从中受益,以改善他们的案件。本文提出了一种利用人脸特征进行年龄估计的高效智能系统。人脸信息采用深度学习技术,即基于卷积神经网络的迁移学习来估计人的年龄。该方法包含预训练模型、卷积基和分类器。所提出的方法是有效的,而且是最先进的技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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