Feature Article: Abandoned Abandoned Object Detection Using HLDNet HLDNet: Abandoned Object Detection Using Hand Luggage Detection Network Dohun Kim, Heegwang Kim, Yeongheon Mok, and Joonki Paik Chung-Ang University Abstract-Abandoned object detection has recently been studied to detect dangerous situations such as illegally dumping explosives. Existing abandoned object detection used background subtraction, which is sensitive to noise and clutters of a similar size in outdoor environments. Unlike existing approaches, this article presents a deep learningbased detection method that is suitable for use in outdoor environments because it is robust to ghost effects and illumination changes. The proposed method consists of three parts: 1) pedestrian detection and tracking; 2) hand luggage detection (HLD); and 3) abandoned object decision. Since the proposed method detects the abandoned object through HLD instead of directly detecting the abandoned object itself, we could successfully improve the detection accuracy and robustness. The proposed method can also detect dangerous weapons or restricted hand luggage through HLD. This article presents an intelligent abandoned object detection system that can be applied for consumer applications. Digital Object Identifier 10.1109/MCE.2021.3099288 Date ofpublication 29 July 2021; date ofcurrent version 7June 2022. & VARIOUS COMPUTER VISION techniques have been proposed to analyze abnormal behaviors from video acquired by closed circuit television (CCTV) or internet protocol cameras. Abnormal behavior analysis is a key technology to build an intelligent surveillance system in smart city or July/August 2022 Published by the IEEE Consumer Technology Society 2162-2248 ß 2021 IEEE 45