BROWSE
Detail
Conference Paper
Detection and Register of Illegal Garbage Dumping Action Using the Consecutive Processing and Embedded-NAS
Cited 0 time in 
Share 
Share
- Authors
- Dasong Yu, Jungeun Yoon, Youngjae Lee
- Issue Date
- 2024-07
- Citation
- International Conference on Advanced Video and Signal-based Surveillance (AVSS) 2024, pp.1-8
- Language
- English
- Type
- Conference Paper
- Abstract
- This paper proposes a system that utilizes YOLO and OpenPose for detecting instances of dumping and evaluating the legality of the garbage. By extracting key joints from the human body and calculating distances, dumping activities can be determined, and the effectiveness of this approach has been established through experimental validation. Additionally, the system utilizes deep learning for video analysis to classify the color of dumped garbage. Information regarding illegal dumping is stored in a NAS (Network Attached Storage) system. The proposed system enables simultaneous detection of dumping and assessment of its legality, allowing for the identification of dumpers through stored video. This system offers significant potential for preventing and monitoring illegal garbage dumping
- KSP Keywords
- Human body, Network attached storage(NAS), Stored video, deep learning(DL), experimental validation, simultaneous detection, video analysis