Online Monitoring System of Fish Behavior
- Resource Type
- Conference
- Authors
- Gang Xiao; Wen Zhang; Yong-Liang Zhang; Jiu-Jun Chen; Shan-Shan Huang; Lu-Ming Zhu
- Source
- 제어로봇시스템학회 국제학술대회 논문집. 2011-10 2011(10):1310-1313
- Subject
- Biological monitoring
Adaptive background updating
Artificial immune
Persistent turning walker model
Anomaly detection
- Language
- Korean
- ISSN
- 2005-4750
In order to overcome the defect of physic-chemical monitoring system and enhance the intelligence of biological monitoring technology, an online monitoring system of fish behavior is proposed in this paper. The main contributions of this system are as follows: 1) adaptive background updating algorithm (ABU); 2) automatic camshift tracking algorithm (ACT) with twice searching; 3) particle filter tracking (PFT) algorithm; 4) persistent turning walker (PTW) model; 5) artificial immune algorithm (AIA). This online system is used to monitor and analyse the fish behavior continuously, establish a normal behavior model and detect the anormal behavior. Experimental results show that the system is running stably and has achieved well effect in the simulation environment.