5 accepted papers
Spatio-temporal cues offer a rich source of information for inferring structural and semantic scene properties. A particularly useful representation in computer vision is a spatio-temporal video segmentation. Together with motion, knowledge of depth can substantially improve superpixel segmentation.
In this paper we give an evaluation of different direct methods for computing frame-to-frame motion estimates of a moving sensor rig composed of an RGB-D camera and an inertial measurement unit. In particular, we compare how semi-dense and fully dense tracking methods, with and without the aid of an…
As robots continue to create long-term maps, the amount of information that they need to handle increases over time. In terms of place recognition, this implies that the number of images being considered may increase until exceeding the computational resources of the robot. In this paper we consider…
A framework for online simultaneous localization, mapping and self-calibration is presented which can detect and handle significant change in the calibration parameters. Estimates are computed in constant-time by factoring the problem and focusing on segments of the trajectory that are most informat…
We present an unsupervised framework for simultaneous appearance-based object discovery, detection, tracking and reconstruction using RGBD cameras and a robot manipulator. The system performs dense 3D simultaneous localization and mapping concurrently with unsupervised object discovery. Putative obj…