This work considers online optimal motion planning of an autonomous agent subject to linear temporal logic (LTL) constraints. The environment is dynamic in the sense containing mobile obstacles and time-varying areas interest (i.e., reward workspace properties) be visited by agent. Since user-specified tasks may not fully realized partially infeasible), this hard soft LTL constraints, where con...

Self-supervised monocular depth estimation approaches suffer not only from scale ambiguity but also infer temporally inconsistent maps w.r.t. scale. While disambiguating during training is possible without some kind of ground truth supervision, having consistent predictions would make it to calculate once inference as a post-processing step and use over-time. With this goal, set temporal consis...

This paper presents a new theoretical framework for motion segmentation based on the motion of tracked region edges. By considering the visible edges of an object, constraints may be placed on the motion labelling of edges. This enables the most likely region labelling and layer ordering to be established, thus producing a segmentation. An implementation is outlined and demonstrated on test seq...

The motion of sea-ice in Antarctica is studied using QuikSCAT scatterometer imagery using methods from computer vision and image processing such as intensity edges and optical flow (OF). Features are computed as differential invariants based on spatial and temporal derivatives various scales. The first estimates of the motion vector field obtained through optical flow are used as the starting p...