-
Chapter and Conference Paper
Collective Classification for Labeling of Places and Objects in 2D and 3D Range Data
In this paper, we present an algorithm to identify types of places and objects from 2D and 3D laser range data obtained in indoor environments. Our approach is a combination of a collective classification meth...
-
Chapter and Conference Paper
Interest Point Detectors for Visual SLAM
In this paper we present several interest points detectors and we analyze their suitability when used as landmark extractors for vision-based simultaneous localization and map** (vSLAM). For this purpose, we...
-
Chapter and Conference Paper
Using AdaBoost for Place Labeling and Topological Map Building
Indoor environments can typically be divided into places with different functionalities like corridors, kitchens, offices, or seminar rooms. We believe that the ability to learn such semantic categories from s...