An Efficient Vision-Based Event Detection Method using Sad & GMM Techniques
In computer vision applications the topic of automated fire detection is an active research. These are not only used in computer vision applications but also used in the closed-circuit television surveillance scenarios with controlled background. In this paper the design of an efficient vision based event detection method for identifying fire in videos is implemented. Earlier, the surveillance applications use static cameras to control the static background. But because of this, there would be no proper event detection and noise also obtained. To overcome this, vision based event detection system is introduced. Here line acquisition, motion segmentation and event detection process is performed. After this all the analysis will be updated with processing time.