Optical flow estimation is one of the oldest and still most active research domains in
computer vision. In 35 years, many methodological concepts have been introduced and …

Many computer vision tasks can be formulated as labeling problems. The desired solution is
often a spatially smooth labeling where label transitions are aligned with color edges of the …

The accuracy of optical flow estimation algorithms has been improving steadily as
evidenced by results on the Middlebury optical flow benchmark. The typical formulation …

While the most accurate solution to off-line structure from motion (SFM) problems is
undoubtedly to extract as much correspondence information as possible and perform batch …

Autonomous navigation for large Unmanned Aerial Vehicles (UAVs) is fairly straight-forward,
as expensive sensors and monitoring devices can be employed. In contrast, obstacle …

In this paper, we solve the problem of estimating dense and accurate depth maps from a
single moving camera. A probabilistic depth measurement is carried out in real time on a per …

State-of-the-art video restoration methods integrate optical flow estimation networks to utilize
temporal information. However, these networks typically consider only a pair of consecutive …

The use of mobile robots in search‐and‐rescue and disaster‐response missions has
increased significantly in recent years. However, they are still remotely controlled by expert …

Dense motion estimations obtained from optical flow techniques play a significant role in
many image processing and computer vision tasks. Remarkable progress has been made in …

A common problem of optical flow estimation in the multiscale variational framework is that
fine motion structures cannot always be correctly estimated, especially for regions with …