We propose an approach for detecting objects in large-scale range datasets that combines bottom-up and top-down processes. In the bottom-up stage, fast-to-compute local descriptors...
Alexander Patterson, Philippos Mordohai, Kostas Da...
— We present an algorithm for learning 3D object models from partial object observations. The input to our algorithm is a sequence of 3D laser range scans. Models learned from th...
Michael Ruhnke, Bastian Steder, Giorgio Grisetti, ...
In this paper, we report on recent extensions to a surface matching algorithm based on local 3-D signatures. This algorithm was previously shown to be effective in view registrati...
Owen T. Carmichael, Daniel F. Huber, Martial Heber...
In this article we explore the use of methodologies for 3D reconstruction from multiple images to recognize faces. We try to devise a strategy to tackle the problem of recognizing...
This paper presents a geometric approach to recognizing smooth objects from their outlines. We define a signature function that associates feature vectors with objects and baseline...
Svetlana Lazebnik, Amit Sethi, Cordelia Schmid, Da...