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Author (up) Bogdan Raducanu; Fadi Dornaika edit  doi
isbn  openurl
  Title Dynamic Facial Expression Recognition Using Laplacian Eigenmaps-Based Manifold Learning Type Conference Article
  Year 2010 Publication IEEE International Conference on Robotics and Automation Abbreviated Journal  
  Volume Issue Pages 156–161  
  Keywords  
  Abstract In this paper, we propose an integrated framework for tracking, modelling and recognition of facial expressions. The main contributions are: (i) a view- and texture independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker; (ii) the complexity of the non-linear facial expression space is modelled through a manifold, whose structure is learned using Laplacian Eigenmaps. The projected facial expressions are afterwards recognized based on Nearest Neighbor classifier; (iii) with the proposed approach, we developed an application for an AIBO robot, in which it mirrors the perceived facial expression.  
  Address Anchorage; AK; USA;  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1050-4729 ISBN 978-1-4244-5038-1 Medium  
  Area Expedition Conference ICRA  
  Notes OR; MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RaD2010 Serial 1310  
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