Application of YOLO Deep Learning Model for Real Time Abandoned Baggage Detection

AUTHORS: Tossaporn Santad, Piyarat Silapasupphakornwong, Worawat Choensawat, and Kingkarn Sookhanaphibarn

ABSTRACT: We proposed an abandoned-baggage detection system that the baggage was left in public places for security reasons, i.e., subway stations. The proposed system applied the YOLO deep learning model for object detection, and presented a GUI for supporting a parameter setting. With this GUI, the detection system will be invariant to lighting and camera position.

Keywords: cctv, image detection, surveillance, yolo, forensic

LINK: http://mit.itu.bu.ac.th/publications/yolo-2pages_v1.pdf

REFERENCES: 

MLA		Santad, Tossaporn, et al. "Application of YOLO Deep Learning Model for Real Time Abandoned Baggage Detection." 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE). IEEE, 2018.
APA		Santad, T., Silapasupphakornwong, P., Choensawat, W., & Sookhanaphibarn, K. (2018, October). Application of YOLO Deep Learning Model for Real Time Abandoned Baggage Detection. In 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE) (pp. 157-158). IEEE.
ISO 690		SANTAD, Tossaporn, et al. Application of YOLO Deep Learning Model for Real Time Abandoned Baggage Detection. In: 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE). IEEE, 2018. p. 157-158.