Combining Top-down Spatial Reasoning and Bottom-up Object Class Recognition for Scene Understanding
2014 (English)In: Proc. of 2014 IEEE/RSJ International Conference on IntelligentRobots and Systems 2014, IEEE conference proceedings, 2014, 2910-2915 p.Conference paper (Refereed)
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.
Place, publisher, year, edition, pages
IEEE conference proceedings, 2014. 2910-2915 p.
Spatial Relations, Robotics, Learning
IdentifiersURN: urn:nbn:se:kth:diva-156599DOI: 10.1109/IROS.2014.6942963ScopusID: 2-s2.0-84911478657OAI: oai:DiVA.org:kth-156599DiVA: diva2:767263
IEEE/RSJ International Conference on Intelligent Robots and Systems, 14-18 Sept. 2014, Chicago, IL, USA
ProjectsStrandsEuropean Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No 600623
FunderEU, FP7, Seventh Framework Programme
QC 201412052014-12-012014-12-012016-03-17Bibliographically approved