Robust tracking of abrupt motion is a challenging task
in computer vision due to the large motion uncertainty. In
this paper, we propose a stochastic approximation Monte
Carlo (...
A new paradigm for the efficient color-based tracking of objects seen from a moving camera is presented. The proposed technique employs the mean shift analysis to derive the targe...
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and po...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
We address the problem of robust appearance-based visual tracking. First, a set of simplified biologically inspired features (SBIF) is proposed for object representation and the B...
We present an algorithm for multi-person tracking-bydetection
in a particle filtering framework. To address the
unreliability of current state-of-the-art object detectors, our
a...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...