A growing number of missing person cases remain unresolved, but machine learning (ML) is helping law enforcement solve these mysteries faster. A new project utilizes facial recognition and ML algorithms like SVM and KNN to identify missing persons based on various features such as gender, age, and location. By training a model with data from Kaggle, the system can accurately match faces, even years after a person goes missing, helping locate children and adults faster.
The system is designed for use by police: they upload a picture of a missing person, and the model compares it with stored images to match the person, even if their appearance has changed. If no match is found, the photo is flagged for further investigation. This system not only accelerates the search process but also supports the identification of missing persons in cases of trafficking or abduction, saving time for both the police and the public.
Read the full paper here: https://www.ijraset.com/research-paper/missing-person-identification-using-ml-algorithms
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