Artificial intelligence publications

The Fundamental matrix is a key concept when working with uncalibrated images and multiple viewpoints. It contains all the available geometric information and enables to recover the epipolar geometry from…

Studies experimentally the problem of computing the position of the epipoles in a pair of uncalibrated images; three families of methods are successively considered.

This paper addresses the problem of accurately and automatically recovering the epipolar geometry from an uncalibrated stereo rig and its application to the image matching problem.

Universal attachment is a domain-independent mechanism for integrating diverse representation and reasoning methods into hybrid frameworks that contain a subsystem based on deduction over logical formulas.

PEWS combines a proven project reporting methodology with the latest artificial intelligence techniques such as evidential reasoning. Together, they ensure the successful outcome of large projects.

We address in this paper the problem of self-calibration and metric reconstruction (up to a scale) from one unknown motion of an uncalibrated stereo rig.

In this paper, we propose an alternative method to compute at the same time camera calibration and motion, which is robust and efficient.

We examine five greedy hillclimbing procedures that search for attribute sets that generalize well with ID3/C4.5. Experiments suggest hillclimbing in attribute space can yield substantial improvements in generalization performance.

Keywords: Artificial Intelligence, Artificial Intelligence Center, AIC