The rapid growth of location-based applications has spurred extensive research on localization. Nonetheless, indoor localization remains an elusive problem mostly because the accu...
Souvik Sen, Romit Roy Choudhury, Srihari Nelakudit...
This paper addresses scene understanding in the context of a moving camera, integrating semantic reasoning ideas from monocular vision with 3D information available through struct...
—CENTRIST (CENsus TRansform hISTogram), a new visual descriptor for recognizing topological places or scene categories, is introduced in this paper. We show that place and scene ...
We present a strategy that combines color and depth images to detect people in indoor environments. Similarity of image appearance and closeness in 3D position over time yield weig...
— Mobile wireless sensors in indoor environments will experience multipath fading, causing rapid variations in the capacity of the radio link. We present a strategy that increase...
We present an approach for creating conceptual representations of human-made indoor environments using mobile robots. The concepts refer to spatial and functional properties of ty...
This paper considers a robot with multiple sensors navigating an unknown, heterogeneous environment. In these cases sensor errors may produce an unsuitable model of the world. For...
Precise digital 3D models of indoor environments are needed in several applications, e.g., facility management, architecture, rescue and inspection robotics. This paper presents a...
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 c...
This paper addresses the problem of building large-scale maps of indoor environments with mobile robots. It proposes a statisticalapproach that phrases the map buildingproblem as ...