期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2021
卷号：99
期号：18
语种：English
出版社：Journal of Theoretical and Applied
摘要：A countless number of persons, including children, teenagers, adults, and mentally challenged people, go missing every day. Some are victims of kidnap and human trafficking, while others got missing in unfamiliar places. Effectively identifying people has always been a fascinating sub-ject, both in industry and research. The majority of proposed solutions have not considered the possibility of using cameras in public places for detecting the faces of missing persons in real-time. Therefore, this paper presents implementing a Haar Cascade Classifier Based Deep-Dataset Face Recognition Algorithm on cameras to locate missing persons in public and notify law en-forcement of missing persons found. This research study employs the in-depth learning approach using Open Computer Vision to automate searching for missing persons using public cameras, thereby improving security, safety, and reducing the time taken to find missing persons. The im-plemented system is the solution to a closed-set problem where the proposed algorithm assumes a deep dataset gallery of the trained face image of missing persons. The real-time implementation of the trained face recognition algorithm gave an average experimental accuracy of 72.9%.
