5 papers · 1 filter
Unsupervised Learning of Shape Concepts - From Real-World Objects to Mental Simulation
Christian A. Mueller, Andreas Birk
An unsupervised shape analysis is proposed to learn concepts reflecting shape commonalities. Our approach is two-fold: i) a spatial topology analysis of point cloud segment constel…
CADDY Underwater Stereo-Vision Dataset for Human-Robot Interaction (HRI) in the Context of Diver Activities
Arturo Gomez Chavez, Andrea Ranieri, Davide Chiarella +3
In this article we present a novel underwater dataset collected from several field trials within the EU FP7 project "Cognitive autonomous diving buddy (CADDY)", where an Autonomous…
Underwater Image Haze Removal and Color Correction with an Underwater-ready Dark Channel Prior
Tomasz Łuczyński, Andreas Birk
Underwater images suffer from extremely unfavourable conditions. Light is heavily attenuated and scattered. Attenuation creates change in hue, scattering causes so called veiling l…
Visual Object Categorization Based on Hierarchical Shape Motifs Learned From Noisy Point Cloud Decompositions
Christian A. Mueller, Andreas Birk
Object shape is a key cue that contributes to the semantic understanding of objects. In this work we focus on the categorization of real-world object point clouds to particular sha…
Conceptualization of Object Compositions Using Persistent Homology
Christian A. Mueller, Andreas Birk
A topological shape analysis is proposed and utilized to learn concepts that reflect shape commonalities. Our approach is two-fold: i) a spatial topology analysis of point cloud se…