We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
This paper presents an analysis of the design of classifiers for use in a hierarchical object recognition approach. In this approach, a cascade of classifiers is arranged in a tr...
Bjoern Stenger, Arasanathan Thayananthan, Philip H...
The classification of urban landscape in aerial LiDAR point clouds is useful in 3D modeling and object recognition applications in urban environments. In this paper, we introduce ...
This paper addresses view-invariant object detection and pose estimation from a single image. While recent work focuses on object-centered representations of point-based object fe...
3D vision guided manipulation of components is a key problem of industrial machine vision. In this paper, we focus on the localization and pose estimation of known industrial objec...