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Ethnicity Recognition Under Difficult Scenarios Using HOG

机译:使用猪的艰难情景下的种族认可

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With the rapid advance of globalization, analyzing nationality and race/ethnicity groups is becoming an emerging research topic that has multi-disciplinary real-world applications such as surveillance systems and targeted advertisements. This paper presents an approach to automatically predict the ethnicity groups of individuals based on their facial characteristics. Several ethnicity groups are considered in this study including: Asian, Indian, and others (like Hispanic, Latino and Middle Eastern). The proposed approach extracts features based on the Histogram of Oriented Gradients (HOG) texture descriptor. Then, it trains a support vector machine (SVM) to detect ethnicity with promising achievable results when evaluated on a publicly available dataset of labelled images.
机译:随着全球化的快速发展,分析国籍和种族/种族群体正在成为一个新兴的研究主题,具有多学科的现实世界应用,如监督系统和有针对性的广告。 本文提出了一种基于面部特征自动预测个人种族群体的方法。 本研究考虑了几个种族群体,包括:亚洲,印度和其他人(如西班牙裔,拉丁裔和中东)。 所提出的方法基于面向梯度(HOG)纹理描述符的直方图提取特征。 然后,它培训了一个支持向量机(SVM),以检测种族,当在标记图像的公开数据集上进行评估时,可实现的可实现结果。

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