More and more applications (path planning, collision avoidance
methods) require 3D description of the surround world. This paper
describes a stereo vision system that uses 2D (grayscale or color) images
to extract simple 2D geometric entities (points, lines) applying a
low-level feature detector. The features are matched across views with a
graph matching algorithm. During the projective reconstruction the 3D
description of the scene is recovered. The developed system uses uncalibrated
cameras, therefore only projective 3D structure can be detected
defined up to a collineation. Using the Euclidean information about a
known set of predefined objects stored in database and the results of the
recognition algorithm, the description can be updated to a metric one
