In this paper, a new approach for object detection and pose estimation is introduced. The contribution consists in the conception of entities permitting stable detection and relia...
Stefan Hinterstoisser, Selim Benhimane, Nassir Nav...
We propose a novel and robust model to represent and learn generic 3D object categories. We aim to solve the problem of true 3D object categorization for handling arbitrary rotati...
Many parameter estimation methods used in computer vision are able to utilise covariance information describing the uncertainty of data measurements. This paper considers the valu...
Michael J. Brooks, Wojciech Chojnacki, Darren Gawl...
In many cases self-calibration is not able to yield a unique solution for the 3D reconstruction of a scene. This is due to the occurrence of critical motion sequences. If this is ...
Camera calibration is a primary crucial step in many computer vision tasks. In this paper we present a new neural approach for camera calibration. Unlike some existing neural appr...