Many robot perception systems are built to only consider intrinsic object features to recognise the class of an object. By integrating both top-down spatial relational reasoning and bottom-up object class recognition the overall performance of a perception system can be improved. In this paper we present a unified framework that combines a 3D object class recognition system with learned, spatial models of object relations. In robot experiments we show that our combined approach improves the classification results on real world office desks compared to pure bottom-up perception. Hence, by using spatial knowledge during object class recognition perception becomes more efficient and robust and robots can understand scenes more effectively. ; QC 20141205 ; Strands ; European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No 600623
Combining Top-down Spatial Reasoning and Bottom-up Object Class Recognition for Scene Understanding
2014-01-01
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Learning Task-Specific Object Recognition and Scene Understanding
British Library Online Contents | 2000
|Scene Understanding by Reasoning Stability and Safety
British Library Online Contents | 2015
|Combining monoSLAM with object recognition for scene augmentation using a wearable camera
British Library Online Contents | 2010
|Image Understanding using vision and reasoning through Scene Description Graph
British Library Online Contents | 2018
|