Package Theft Detection from Smart Home Security Cameras

Hung-Min Hsu, Xinyu Yuan, Baohua Zhu, Zhongwei Cheng, Lin Chen
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引用次数: 0

Abstract

Package theft detection has been a challenging task mainly due to lack of training data and a wide variety of package theft cases in reality. In this paper, we propose a new Global and Local Fusion Package Theft Detection Embedding (GLF-PTDE) framework to generate package theft scores for each segment within a video to fulfill the real-world requirements on package theft detection. Moreover, we construct a novel Package Theft Detection dataset to facilitate the research on this task. Our method achieves 80% AUC performance on the newly proposed dataset, showing the effectiveness of the proposed GLF-PTDE framework and its robustness in different real scenes for package theft detection.
智能家庭安全摄像头的包裹盗窃检测
由于缺乏训练数据和现实中各种各样的包裹盗窃案件,包裹盗窃检测一直是一项具有挑战性的任务。在本文中,我们提出了一个新的全局和局部融合包盗窃检测嵌入(GLF-PTDE)框架来生成视频中每个片段的包盗窃分数,以满足现实世界对包盗窃检测的要求。此外,我们还构建了一个新的包裹盗窃检测数据集来促进这项任务的研究。我们的方法在新提出的数据集上达到了80%的AUC性能,表明了所提出的GLF-PTDE框架在不同真实场景下的有效性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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