SeekSuspect: retrieving suspects from criminal datasets using visual memory

Aayush Jain, Meet Shah, Suraj Pandey, Mansi Agarwal, Rajiv Ratn Shah, Yifang Yin

Abstract: It is crucial for the police department to automatically determine if suspects are present in the criminal database, sometimes based on the informant's visual memory alone. FaceFetch [15] is a state-of-the-art face retrieval system capable of retrieving an envisioned face from a large-scale database. Although FaceFetch can retrieve images effectively, it lacks sophisticated techniques to produce results efficiently. To this end, we propose SeekSuspect, a faster interactive suspect retrieval framework, which introduces several optimization algorithms to FaceFetch's framework. We train and test our system on a real-world dataset curated in collaboration with a metropolitan police department in India. Results reveal that SeekSuspect beats FaceFetch and can be employed by law enforcement agencies to retrieve suspects.