상세정보
학술대회
Human-skeleton based Fall-Detection Method using LSTM for Manufacturing Industries
- 발행일
- 201906
- 출처
- International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) 2019, pp.1-4
- 협약과제
- 19MS1200, SW통합 개발자 환경(SDK) 및 공통 라이브러리 개발, 나갑주
- 초록
- According to the statistics of the Korea Occupational Safety Health Agency, the incidences of falls in the manufacturing industry are increasing. In this paper, we introduce a fall-detection method based on skeleton data obtained from a 2D RGB CCTV Camera installed on the manufacturing floor. We proposed feature-extraction methods to improve of fall-detection accuracy and the construction of a fall-detection system using LSTM. Experiments were conducted through public datasets (URFD and SDUFall) to find feature-extraction methods that can achieve high classification accuracy. The experimental results showed that the proposed method is more effective in detecting falls than raw skeleton data which are not processed anything.
- KSP 제안 키워드
- CCTV Camera, Detection Method, Detection accuracy, Extraction method, Fall Detection, Feature extractioN, Intrusion detection system(IDS), Occupational safety, Public Datasets, Skeleton data, classification accuracy