We propose a sequential Monte Carlo data association algorithm based on a two-level computational framework for tracking varying number of interacting objects in dynamic scene. Fi...
We present a generative model and stochastic filtering algorithm for simultaneous tracking of 3D position and orientation, non-rigid motion, object texture, and background texture...
Tim K. Marks, John R. Hershey, J. Cooper Roddey, J...
A new method for object tracking in video sequences is presented. This method exploits the benefits of particle filters to tackle the multimodal distributions emerging from clutte...
Alexandros Makris, Dimitrios I. Kosmopoulos, Stavr...
This paper presents a new approach for region-based video mosaicing, treating moving objects separately from the background, and with improved ghost-like noise elimination. The mo...
Tomio Echigo, Richard J. Radke, Peter J. Ramadge, ...
The problem of detecting areas of motion in video sequences and estimating parameters such as speed, direction and dynamics is addressed in many applications of image processing s...