Integration of visual and shape attributes for object action complexes

Authors:
Kai Huebner;Mårten Björkman;Babak Rasolzadeh;Martina Schmidt;Danica Kragic
Affiliations:
KTH-Royal Institute of Technology, Stockholm, Computer Vision & Active Perception Lab, Sweden;KTH-Royal Institute of Technology, Stockholm, Computer Vision & Active Perception Lab, Sweden;KTH-Royal Institute of Technology, Stockholm, Computer Vision & Active Perception Lab, Sweden;KTH-Royal Institute of Technology, Stockholm, Computer Vision & Active Perception Lab, Sweden;KTH-Royal Institute of Technology, Stockholm, Computer Vision & Active Perception Lab, Sweden
Venue:
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Year:
2008

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Abstract

Our work is oriented towards the idea of developing cognitive capabilities in artificial systems through Object Action Complexes (OACs) [7]. The theory comes up with the claim that objects and actions are inseparably intertwined. Categories of objects are not built by visual appearance only, as very common in computer vision, but by the actions an agent can perform and by attributes perceivable. The core of the OAC concept is constituting objects from a set of attributes, which can be manifold in type (e.g. color, shape, mass, material), to actions. This twofold of attributes and actions provides the base for categories. The work presented here is embedded in the development of an extensible system for providing and evolving attributes, beginning with attributes extractable from visual data.