  This paper presents Diver Interest via Pointing in Three Dimensions (DIP-3D),
a method to relay an object of interest from a diver to an autonomous
underwater vehicle (AUV) by pointing that includes three-dimensional distance
information to discriminate between multiple objects in the AUV's camera image.
Traditional dense stereo vision for distance estimation underwater is
challenging because of the relative lack of saliency of scene features and
degraded lighting conditions. Yet, including distance information is necessary
for robotic perception of diver pointing when multiple objects appear within
the robot's image plane. We subvert the challenges of underwater distance
estimation by using sparse reconstruction of keypoints to perform pose
estimation on both the left and right images from the robot's stereo camera.
Triangulated pose keypoints, along with a classical object detection method,
enable DIP-3D to infer the location of an object of interest when multiple
objects are in the AUV's field of view. By allowing the scuba diver to point at
an arbitrary object of interest and enabling the AUV to autonomously decide
which object the diver is pointing to, this method will permit more natural
interaction between AUVs and human scuba divers in underwater-human robot
collaborative tasks.
