Analysis of spatial structures in robotic environments, especially structures such as planar
surfaces, has become a fundamental component in diverse robot vision systems since the …

Spatial structure, typically dealt with by robots in domestic environments conform to
Manhattan spatial orientations. In other words, much of the 3D point cloud space conform to …

In order to estimate multiple structures without prior knowledge of the noise scale, this paper
utilizes Jensen-Shannon Divergence (JSD), which is a similarity measurement method, to …

After a brief lull in the 1990s, robotics has become resurgent thanks to advancements in
robotic autonomy made implementable through hyper fast, cheap, multithreaded computing …

In this paper a method for inferring 3D structure information based on both range and visual
data is proposed. Data fusion is achieved by validating assumptions formed according to 2D …

We present an approach for estimating occupancy grids with an emphasis on robotics
applications, where collision avoidance and robustness to severe noise are of more …

We propose a new method of indoor-scene stereo vision that uses probabilistic prior
knowledge of indoor scenes in order to exploit the global structure of artificial objects. In our …

In this paper we propose a novel approach for the robust estimation of room structure using
Manhattan world assumption ie the frequently observed dominance of three mutually …

In this paper, a method for inferring scene structure information based on both laser and
visual data is proposed. Common laser scanners employed in contemporary robotic systems …

This book presents a statistical learning framework for inferring geometric structures from
images. The proposed framework computes dense range maps of locations in the …