Recognizing Object Affordances in Terms of Spatio-Temporal Object-Object Relationships
2014 (English)In: Humanoid Robots (Humanoids), 2014 14th IEEE-RAS International Conference on, IEEE conference proceedings, 2014, 52-58 p.Conference paper (Refereed)
In this paper we describe a probabilistic framework that models the interaction between multiple objects in a scene.We present a spatio-temporal feature encoding pairwise interactions between each object in the scene. By the use of a kernel representation we embed object interactions in a vector space which allows us to define a metric comparing interactions of different temporal extent. Using this metric we define a probabilistic model which allows us to represent and extract the affordances of individual objects based on the structure of their interaction. In this paper we focus on the presented pairwise relationships but the model can naturally be extended to incorporate additional cues related to a single object or multiple objects. We compare our approach with traditional kernel approaches and show a significant improvement.
Place, publisher, year, edition, pages
IEEE conference proceedings, 2014. 52-58 p.
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:kth:diva-158008DOI: 10.1109/HUMANOIDS.2014.7041337ScopusID: 2-s2.0-84945185392OAI: oai:DiVA.org:kth-158008DiVA: diva2:773367
International Conference on Humanoid Robots,November 18-20th 2014, Madrid, Spain
QC 201412232014-12-182014-12-182015-05-04Bibliographically approved