Track 3 – Image, Speech, Signal and Video Processing

07 Dic 2016
14:00 - 15:00
Gran Cancun T1

Track 3 – Image, Speech, Signal and Video Processing

A Future for Learning Semantic Models of Man-Made Environments

Deriving semantic 3D models of man-made environments hitherto has not reached the desired maturity which makes human interaction obsolete.
Man-made environments play a central role in navigation, city planning, building management systems, disaster management or augmented reality.
They are characterised by rich geometric and semantic structures. These cause conceptual problems when learning generic models or when developing automatic acquisition systems.

These conceptual problems are caused by the interplay between (1) the elementary data structures of the 3D objects and the observed images or 3D point clouds, (2) the topology of the rich spatial structures, (3) the partonomy and taxonomy of complex objects, and (4) the uncertainty and qualitativeness of the used notions in the envisaged application domains.

The paper sketches some research issues in conceptual modelling playing a key role for a further evolution of acquiring man-made environments from visual data.