Tatsuki Tamano, Ryuya Itano, Honoka Tanitsu, Takahiro Koita

Proceedings of the 28th World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2024, pp. 51-53 (2024); https://doi.org/10.54808/WMSCI2024.01.51

Tatsuki Tamano
Graduate School of Science and Engineering, Doshisha University, Kyotanabe, Kyoto, Japan

Ryuya Itano
Graduate School of Science and Engineering, Doshisha University, Kyotanabe, Kyoto, Japan

Honoka Tanitsu
Graduate School of Science and Engineering, Doshisha University, Kyotanabe, Kyoto, Japan

Takahiro Koita
Graduate School of Science and Engineering, Doshisha University, Kyotanabe, Kyoto, Japan

Cite this paper as:
Tamano, T., Itano, R., Tanitsu, H., Koita, T. (2024). Crime Detection Method Using Multiple Anomaly Detection Models and Crowdsourcing. In N. Callaos, E. Gaile-Sarkane, N. Lace, B. Sánchez, M. Savoie (Eds.), Proceedings of the 28th World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2024, pp. 51-53. International Institute of Informatics and Cybernetics. https://doi.org/10.54808/WMSCI2024.01.51

In recent years, the crime clearance rate has remained at a low level. The constant human monitoring of surveillance camera videos is expected to improve crime arrest rates. However, constantly monitoring of surveillance camera videos requires a large number of workers. There is an existing method for crime detection with a small number of workers that combines a single anomaly detection model with crowdsourcing. However, existing method misses crimes in anomaly detection model layer. Therefore, we propose a new method that prevents the miss of crimes by using multiple anomaly detection models and crowdsourcing. We discuss the expected benefits of our proposed method and future plans for our proposed method.