Modeling and recognition of actions through motor primitives
2008 (English)In: 2008 IEEE International Conference On Robotics And Automation: Vols 1-9, 2008, 1704-1709 p.Conference paper (Refereed)
We investigate modeling and recognition of object manipulation actions for the purpose of imitation based learning in robotics. To model the process, we are using a combination of discriminative (support vector machines, conditional random fields) and generative approaches (hidden Markov models). We examine the hypothesis that complex actions can be represented as a sequence of motion or action primitives. The experimental evaluation, performed with five object manipulation actions and 10 people, investigates the modeling approach of the primitive action structure and compares the performance of the considered generative and discriminative models.
Place, publisher, year, edition, pages
2008. 1704-1709 p.
, IEEE International Conference On Robotics And Automation, ISSN 1050-4729
IdentifiersURN: urn:nbn:se:kth:diva-38780DOI: 10.1109/ROBOT.2008.4543446ISI: 000258095001058ScopusID: 2-s2.0-51649098561ISBN: 978-1-4244-1646-2OAI: oai:DiVA.org:kth-38780DiVA: diva2:438626
2008 IEEE International Conference on Robotics and Automation, ICRA 2008; Pasadena, CA; 19 May 2008 through 23 May 2008