In this paper, we present a probabilistic framework for automatic detection and tracking of objects. We address the data association problem by formulating the visual tracking as ...
It is often thought that learning algorithms that track the best solution, as opposed to converging to it, are important only on nonstationary problems. We present three results s...
We present a vision system for the 3-D modelbased tracking of unconstrained human movement. Using image sequences acquired simultaneously from multiple views, we recover the 3-D b...
Man-made environments are abundant with planar surfaces which have attractive properties and are a prerequisite for a variety of vision tasks. This paper presents an incremental m...
Johann Prankl, Michael Zillich, Bastian Leibe, Mar...
Sparse representation has been applied to visual tracking by finding the best candidate with minimal reconstruction error using target templates. However most sparse representati...