Detecting and Counting Oysters
This work addresses oyster restoration monitoring for aquaculture and environmental management, but it is incremental as it applies an existing method to a new domain.
The researchers tackled the problem of monitoring oyster populations in the Chesapeake Bay by using an ROV to capture video and applying Mask R-CNN for detection and tracking to count oysters, achieving automated counting from video footage.
Oysters are an essential species in the Chesapeake Bay living ecosystem. Oysters are filter feeders and considered the vacuum cleaners of the Chesapeake Bay that can considerably improve the Bay's water quality. Many oyster restoration programs have been initiated in the past decades and continued to date. Advancements in robotics and artificial intelligence have opened new opportunities for aquaculture. Drone-like ROVs with high maneuverability are getting more affordable and, if equipped with proper sensory devices, can monitor the oysters. This work presents our efforts for videography of the Chesapeake bay bottom using an ROV, constructing a database of oysters, implementing Mask R-CNN for detecting oysters, and counting their number in a video by tracking them.