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Author David Sanchez-Mendoza; David Masip; Agata Lapedriza edit   file
doi  openurl
  Title Emotion recognition from mid-level features Type Journal Article
  Year 2015 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 67 Issue (down) Part 1 Pages 66–74  
  Keywords Facial expression; Emotion recognition; Action units; Computer vision  
  Abstract In this paper we present a study on the use of Action Units as mid-level features for automatically recognizing basic and subtle emotions. We propose a representation model based on mid-level facial muscular movement features. We encode these movements dynamically using the Facial Action Coding System, and propose to use these intermediate features based on Action Units (AUs) to classify emotions. AUs activations are detected fusing a set of spatiotemporal geometric and appearance features. The algorithm is validated in two applications: (i) the recognition of 7 basic emotions using the publicly available Cohn-Kanade database, and (ii) the inference of subtle emotional cues in the Newscast database. In this second scenario, we consider emotions that are perceived cumulatively in longer periods of time. In particular, we Automatically classify whether video shoots from public News TV channels refer to Good or Bad news. To deal with the different video lengths we propose a Histogram of Action Units and compute it using a sliding window strategy on the frame sequences. Our approach achieves accuracies close to human perception.  
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  Publisher Elsevier B.V. Place of Publication Editor  
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  Series Volume Series Issue Edition  
  ISSN 0167-8655 ISBN Medium  
  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ SML2015 Serial 2746  
Permanent link to this record
 
 
Author David Guillamet; Jordi Vitria edit  doi
openurl 
  Title Evaluation of distance metrics for recognition based on non-negative matrix factorization Type Journal Article
  Year 2003 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 24 Issue (down) 9-10 Pages 1599 –1605  
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  Abstract IF: 0.809  
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  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ GuV2003b Serial 380  
Permanent link to this record
 
 
Author A. Martinez; Jordi Vitria edit  doi
openurl 
  Title Learning mixture models using a genetic version of the EM algorithm. Type Journal Article
  Year 2000 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 21 Issue (down) 8 Pages 759–769  
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  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ MVi2000 Serial 335  
Permanent link to this record
 
 
Author Bogdan Raducanu; Jordi Vitria edit  openurl
  Title Learning to Learn: From Smarts Machines to Intelligent Machines Type Journal
  Year 2008 Publication Patter Recognition Letters Abbreviated Journal PRL  
  Volume 29 Issue (down) 8 Pages 1024–1032  
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  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RaV2008a Serial 950  
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Author Mario Rojas; David Masip; A. Todorov; Jordi Vitria edit  url
doi  openurl
  Title Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models Type Journal Article
  Year 2011 Publication PloS one Abbreviated Journal Plos  
  Volume 6 Issue (down) 8 Pages e23323  
  Keywords  
  Abstract JCR Impact Factor 2010: 4.411
Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions		  
  Address  
  Corporate Author Thesis  
  Publisher Public Library of Science Place of Publication Editor  
  Language Summary Language Original Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ RMT2011 Serial 1883  
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