SeekSuspect : Retrieving Suspects from Criminal Datasets using Visual Memory
Published in The Second ACM International Conference on Multimedia in Asia: Demo Papers., 2021
Recommended citation: Aayush Jain*, Meet Shah*, Suraj Pandey*, Mansi Agarwal*, Rajiv Ratn Shah, Yifang Yin. The Second ACM International Conference on Multimedia in Asia: Demo Papers. ACMM 2021.
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 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.