Exploiting and modeling local 3D structure for predicting object locations
2012 (English)In: Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on, IEEE , 2012, 3885-3892 p.Conference paper (Refereed)
In this paper, we argue that there is a strong correlation between local 3D structure and object placement in everyday scenes. We call this the 3D context of the object. In previous work, this is typically hand-coded and limited to flat horizontal surfaces. In contrast, we propose to use a more general model for 3D context and learn the relationship between 3D context and different object classes. This way, we can capture more complex 3D contexts without implementing specialized routines. We present extensive experiments with both qualitative and quantitative evaluations of our method for different object classes. We show that our method can be used in conjunction with an object detection algorithm to reduce the rate of false positives. Our results support that the 3D structure surrounding objects in everyday scenes is a strong indicator of their placement and that it can give significant improvements in the performance of, for example, an object detection system. For evaluation, we have collected a large dataset of Microsoft Kinect frames from five different locations, which we also make publicly available.
Place, publisher, year, edition, pages
IEEE , 2012. 3885-3892 p.
, IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
Intelligent systems, Object recognition, Three dimensional computer graphics
IdentifiersURN: urn:nbn:se:kth:diva-111533DOI: 10.1109/IROS.2012.6386111ISI: 000317042704070ScopusID: 2-s2.0-84872355812ISBN: 978-1-4673-1737-5OAI: oai:DiVA.org:kth-111533DiVA: diva2:586980
25th IEEE/RSJ International Conference on Robotics and Intelligent Systems, IROS 2012; Vilamoura, Algarve;7 October 2012 through 12 October 2012
FunderICT - The Next Generation
QC 201301292013-01-132013-01-132013-06-18Bibliographically approved