Echosounder tracking with monocular camera for biomass estimation

Echosounders are employed in sea-based aquaculture to estimate the biomass present in a net pen. Knowing the position of the echosounder within the net pen over time, and monitoring its status are required to assess the quality of the biomass density measured by the instrument. This paper studies how to track the position of the echosounder placed inside the fish cage using the monocular camera of an ROV, and provides a solution verified to work even on a small dataset. The methodology for achieving localization of the echosounder is divided into two separate tasks: detection with tracking and pose estimation. A dataset of about 1000 labelled images has been used to train the YOLO v5 detection framework. Once the object is detected, DeepSort is used to track the echosounder. The combination YOLO - DeepSort is furthermore robust to short periods (up to a few seconds) of full occlusion thanks to DeepSort emplyoing a Kalman filter. The pose estimation task relies on beforehand known information (i.e., the dimensions of the echosounder, and the camera calibration parameters) as well as the position of the object in the image frame determined by the detection and tracking systems. Standard image processing techniques are employed to estimate the ellipse shape of the echosounder. The ellipse parameters, the echosounder dimensions and the camera parameters are used to estimate the position of the echosounder with respect to the ROV camera.