Package Theft Detection from Smart Home Security Cameras
This addresses package theft for smart home security users, but it is incremental as it builds on existing detection methods with a new dataset and framework.
The paper tackles package theft detection from smart home security cameras by proposing a Global and Local Fusion Package Theft Detection Embedding (GLF-PTDE) framework and constructing a new dataset, achieving 80% AUC performance.
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.