Title
Identifying objects from hand configurations during in-hand exploration
Abstract
In this work we use hand configuration and contact points during in-hand object exploration to identify the manipulated objects. Different contact points associated to an object shape can be represented in a latent space and lie on a lower dimensional non-linear manifold in the contact points space which is suitable for modelling and recognition. Associating and learning hand configurations to specific objects by means of Gaussian mixture models, later by identifying the hand configuration during the in-hand object exploration we can generate hypotheses of candidate objects to be identified. This process selects a set of the most probable objects from a database. The accumulated set of contact points (partial volume of the object shape) during the object in-hand exploration is matched to the set selected from the database (most probable candidate objects). Results are presented for human manipulation of objects, but this can also be applied to artificial hands, although we have not addressed the hand control, only the object identification.
Year
DOI
Venue
2012
10.1109/MFI.2012.6343033
Multisensor Fusion and Integration for Intelligent Systems
Keywords
Field
DocType
gaussian processes,image representation,object recognition,shape recognition,gaussian mixture models,artificial hands,contact point space,hand configuration learning,human object manipulation,in-hand object exploration,latent space,lower dimensional nonlinear manifold,object identification,object manipulation,object shape representation,probable candidate objects,shape,computational modeling,probabilistic logic,databases
Object-oriented design,Computer science,Artificial intelligence,Deep-sky object,Computer vision,Active shape model,3D single-object recognition,Pattern recognition,Method,Object model,Object-based spatial database,Machine learning,Cognitive neuroscience of visual object recognition
Conference
ISBN
Citations 
PageRank 
978-1-4673-2511-0
2
0.37
References 
Authors
6
3
Name
Order
Citations
PageRank
Diego R. Faria19514.96
Jorge Lobo233831.84
Jorge Dias355651.00