A clustering system utilizing acquired age and gender demographics thru facial detection and recognition technology

Alvin Titus R. Angus, John Alvin P. Guillen, Maurice Laurence G. Lenon, Ray Justin C. Principe, Gerald P. Feudo, Kanny Krizzy D. Serrano
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Abstract

Clustering has become relevant to an increasing amount of applications, particularly since the rise of social platforms and electronic marketing. Nevertheless, performance of existing methods on real-world images is still significantly lacking, especially when compared to the tremendous leaps in performance recently reported for the related task of facial recognition and classification. Our design for a Clustering system asses a particular group on what type of relation they have from each other, this system takes advantage of both demographic information taken from facial recognition and the interpersonal distance of the audience from one another.
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通过人脸检测和识别技术,利用获得的年龄和性别人口统计数据的聚类系统
集群已经与越来越多的应用程序相关,特别是在社交平台和电子营销兴起之后。然而,现有方法在真实世界图像上的性能仍然显着不足,特别是与最近报道的面部识别和分类相关任务的性能巨大飞跃相比。我们设计的聚类系统评估了特定群体彼此之间的关系类型,该系统利用了从面部识别中获得的人口统计信息和观众之间的人际距离。
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