This paper describes a new method for estimating optical flow that strikes a balance between the flexibility of local dense computations and the robustness and accuracy of global ...
We present an online learning approach for robustly combining unreliable
observations from a pedestrian detector to estimate the rough 3D scene geometry
from video sequences of a...
Michael D. Breitenstein, Eric Sommerlade, Bastian ...
We present a robust framework for estimating non-rigid 3D shape and motion in video sequences. Given an input video sequence, and a user-specified region to reconstruct, the algori...
We derive a probabilistic framework for robust, realtime, visual tracking of multiple previously unseen objects from a moving camera. This framework models the discrete depth orde...
The mean shift algorithm has achieved considerable success in object tracking due to its simplicity and robustness. It finds local minima of a similarity measure between the color...
Changjiang Yang, Ramani Duraiswami, Larry S. Davis