Marine vessel tracking using a monocular camera
This provides a real-time, low-power solution for marine vessel tracking in IoT environments, though it is incremental as it builds on existing monocular tracking methods.
The paper tackles the problem of tracking marine vessels from a monocular camera by introducing a new camera calibration technique using only GPS data and estimating distance from bounding box location and size, achieving an average prediction error of 5.55m per 100m distance.
In this paper, a new technique for camera calibration using only GPS data is presented. A new way of tracking objects that move on a plane in a video is achieved by using the location and size of the bounding box to estimate the distance, achieving an average prediction error of 5.55m per 100m distance from the camera. This solution can be run in real-time at the edge, achieving efficient inference in a low-powered IoT environment while also being able to track multiple different vessels.