  We tackle the problem of localizing an autonomous sea-surface vehicle in
river estuarine areas using monocular camera and angular velocity input from an
inertial sensor. Our method is challenged by two prominent drawbacks associated
with the environment, which are typically not present in standard visual
simultaneous localization and mapping (SLAM) applications on land (or air): a)
Scene depth varies significantly (from a few meters to several kilometers) and,
b) In conjunction to the latter, there exists no ground plane to provide
features with enough disparity based on which to reliably detect motion. To
that end, we use the IMU orientation feedback in order to re-cast the problem
of visual localization without the mapping component, although the map can be
implicitly obtained from the camera pose estimates. We find that our method
produces reliable odometry estimates for trajectories several hundred meters
long in the water. To compare the visual odometry estimates with GPS based
ground truth, we interpolate the trajectory with splines on a common parameter
and obtain position error in meters recovering an optimal affine transformation
between the two splines.
