Annotating photographs or videos to identify and distinguish different elements of fires is commonly referred to as “fire annotation.” These annotations are usually utilized for training programs for computer vision and machine learning models to identify and respond to fire-related incidents.
Here are some key aspects of fire annotation:
- Object Detection: It includes marking and outlining the confines of flames or areas affected by fire within an image/video. This helps AI systems identify the presence of a fire.
- Smoke Detection: Smoke annotation involves labelling the areas with smoke that can detect fire.
- Fire Spread: This includes marking the direction and the extent of the fire spread within an image or video sequence. This predicts the behavior of the fire.
- Heat Mapping: Annotation is used to create heat maps showing the intensity and temperature of fires in the images. This data can help in understanding the severity of a fire.
- Training Data: Fire annotation is essential as it acts as training material for the machine learning models. The models learn to recognize fires and make real-time decisions, like alerting the people starting the fire suppression systems.