UNDERSTANDING POSITIONING FROM MULTIPLE IMAGES

It is possible to recover the three-dimensional structure of a scene u sing only correspondences between images taken with uncalibrated camer as (faugeras 1992). The reconstruction obtained this way is only defin ed up to a projective transformation of the 3D space. However, this ki nd of structure allows some spatial reasoning such as finding a path. In order to perform more specific reasoning, or to perform work with a robot moving in Euclidean space, Euclidean or affine constraints have to be added to the camera observations. Such constraints arise from t he knowledge of the scene: location of points, geometrical constraints on lines, etc. First, this paper presents a reconstruction method for the scene, then it discusses how the framework of projective geometry allows symbolic or numerical information about positions to be derive d, and how knowledge about the scene can be used for computing symboli c or numerical relationships. Implementation issues and experimental r esults are discussed.