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Matthias S. Keil; Jordi Vitria |
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Pushing it to the Limit: Adaptation with Dynamically Switching Gain Control |
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2007 |
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EURASIP Journal on Advances in Signal Processing, Vol 2007, Article ID 51684, 10 pages, doi: 10.1155/2007/51684 |
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OR;MV |
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BCNPCL @ bcnpcl @ KeV2007 |
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794 |
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Matthias S. Keil; Agata Lapedriza; David Masip; Jordi Vitria |
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Preferred Spatial Frequencies for Human Face Processing Are Associated with Optimal Class Discrimination in the Machine |
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2008 |
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PLoS ONE 3(7):e2590, DOI:10.1371/journal.pone.0002590 |
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OR;MV |
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BCNPCL @ bcnpcl @ KLM2008 |
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978 |
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Mario Rojas; David Masip; A. Todorov; Jordi Vitria |
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Title |
Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models |
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2011 |
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PloS one |
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6 |
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8 |
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e23323 |
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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 |
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Public Library of Science |
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Admin @ si @ RMT2011 |
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1883 |
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Maria Vanrell; Jordi Vitria; Xavier Roca |
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A multidimensional scaling approach to explore the behavior of a texture perception algorithm. |
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1997 |
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Machine Vision and Applications |
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9 |
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262–271 |
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BCNPCL @ bcnpcl @ VVR1997 |
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35 |
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Maria Vanrell; Jordi Vitria |
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Optimal 3x3 decomposable disks for morphological transformations |
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1997 |
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Image and Vision Computing, 15(2): 845–854 |
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BCNPCL @ bcnpcl @ VaV1997c |
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543 |
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