Abstract. Rivers during floods bring a lot of fallen trees and debris. Video surveillance systems are installed on strategically important places on the rivers. To protect these places from destructions due to accumulation of wood, such systems must be able to automatically detect wood. Image segmentation is performed to separate wood and other moving elements from the rest of the water. Moving objects are detected with respect to brightness and temporal variation features. The floating wood is then tracked in the sequence of frames by temporal linking of the segments generated in the detection step. Our algorithm is tested on multiple videos of floods and the results are evaluated both qualitatively and quantitatively.
Reference REF calculates the intensity and time probability maps of each input image frame and separates the floating wood objects from the water surface with respect to brightness and temporal variation features.
Wood detection and tracking in videos of rivers
SCIA
Computer Science