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Agata Lapedriza; David Masip; Jordi Vitria |
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A Hierarchical Approach for Multi-task Logistic Regression |
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2007 |
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3rd Iberian Conference on Pattern Recognition and Image Analysis |
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4478 |
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258–265 |
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Girona (Spain) |
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J. Marti et al. |
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IbPRIA |
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OR; MV |
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BCNPCL @ bcnpcl @ LMV2007a |
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902 |
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Agata Lapedriza; David Masip; Jordi Vitria |
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Title |
On the Use of External Face Features for Identity Verification |
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2006 |
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Journal of Multimedia, 1(4): 11–20 |
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1 |
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4 |
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11-20 |
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Face Verification, Computer Vision, Machine Learning |
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In general automatic face classification applications images are captured in natural environments. In these cases, the performance is affected by variations in facial images related to illumination, pose, occlusion or expressions. Most of the existing face classification systems use only the internal features information, composed by eyes, nose and mouth, since they are more difficult to imitate. Nevertheless, nowadays a lot of applications not related to security are developed, and in these cases the information located at head, chin or ears zones (external features) can be useful to improve the current accuracies. However, the lack of a natural alignment in these areas makes difficult to extract these features applying classic Bottom-Up methods. In this paper, we propose a complete scheme based on a Top-Down reconstruction algorithm to extract external features of face images. To test our system we have performed face verification experiments using public databases, given that identity verification is a general task that has many real life applications. We have considered images uniformly illuminated, images with occlusions and images with high local changes in the illumination, and the obtained results show that the information contributed by the external features can be useful for verification purposes, specially significant when faces are partially occluded. |
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BCNPCL @ bcnpcl @ LMV2006b |
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708 |
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Agata Lapedriza; David Masip; Jordi Vitria |
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Title |
Face Verification using External Features |
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2006 |
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7th International Conference on Automatic Face and Gesture Recognition (FG´06), 132– 137 |
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Southampton (United Kingdom) |
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BCNPCL @ bcnpcl @ LMV2006a |
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707 |
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Agata Lapedriza; David Masip; Jordi Vitria |
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Are external face features useful for automatic face classification? |
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2005 |
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IEEE Workshop on Face Recognition Grand Challenge Experiments, 151–ff |
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San Diego; CA; USA; |
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BCNPCL @ bcnpcl @ LMV2005b |
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547 |
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Agata Lapedriza; David Masip; Jordi Vitria |
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Title |
The contribution of external features to face recognition |
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2005 |
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Pattern Recognition and Image Analysis (IbPRIA 2005), LNCS 3523: 537–544 |
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Estoril (Portugal) |
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BCNPCL @ bcnpcl @ LMV2005a |
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546 |
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Agata Lapedriza; Jaume Garcia; Ernest Valveny; Robert Benavente; Miquel Ferrer; Gemma Sanchez |
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Title |
Una experiencia de aprenentatge basada en projectes en el ambit de la informatica |
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2008 |
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V Jornades d’Innovacio Docent (UAB) |
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63 |
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Bellaterra (Spain) |
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OR; IAM; DAG; CIC; MV |
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BCNPCL @ bcnpcl @ LGV2008 |
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1030 |
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Author |
Agata Lapedriza; Jordi Vitria |
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Title |
Experimental Study of the Usefulness of External Face Features for Face Classification |
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2005 |
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Artificial Intelligence Research and Development, IOS Press, 99–106 |
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Amsterdam |
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OR;MV |
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BCNPCL @ bcnpcl @ LaV2005 |
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610 |
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Author |
Agata Lapedriza |
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Title |
Multitask Learning Techniques for Automatic Face Classification |
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2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Automatic face classification is currently a popular research area in Computer Vision. It involves several subproblems, such as subject recognition, gender classification or subject verification.
Current systems of automatic face classification need a large amount of training data to robustly learn a task. However, the collection of labeled data is usually a difficult issue. For this reason, the research on methods that are able to learn from a small sized training set is essential.
The dependency on the abundance of training data is not so evident in human learning processes. We are able to learn from a very small number of examples, given that we use, additionally, some prior knowledge to learn a new task. For example, we frequently find patterns and analogies from other domains to reuse them in new situations, or exploit training data from other experiences.
In computer science, Multitask Learning is a new Machine Learning approach that studies this idea of knowledge transfer among different tasks, to overcome the effects of the small sample sized problem.
This thesis explores, proposes and tests some Multitask Learning methods specially developed for face classification purposes. Moreover, it presents two more contributions dealing with the small sample sized problem, out of the Multitask Learning context. The first one is a method to extract external face features, to be used as an additional information source in automatic face classification problems. The second one is an empirical study on the most suitable face image resolution to perform automatic subject recognition. |
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Barcelona (Spain) |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Jordi Vitria;David Masip |
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BCNPCL @ bcnpcl @ Lap2009 |
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1263 |
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Author |
Agata Lapedriza |
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Title |
Face Classification using External Face Features |
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2005 |
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CVC Technical Report #83 |
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BCNPCL @ bcnpcl @ Lap2005 |
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551 |
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Author |
Matthias S. Keil; Agata Lapedriza; David Masip; Jordi Vitria |
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Title |
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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BCNPCL @ bcnpcl @ KLM2008 |
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978 |
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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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BCNPCL @ bcnpcl @ KeV2007 |
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794 |
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Matthias S. Keil; Jordi Vitria |
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Does the brain generate representations of smooth brightness gradients? A novel account for Mach bands, Chevreul’s illusion, and a variant of the Ehrenstein disk |
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2005 |
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European Conference on Visual Perception |
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BCNPCL @ bcnpcl @ KeV2005b |
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607 |
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Matthias S. Keil; Jordi Vitria |
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Does the brain generate representations of smooth brightness gradients? A novel account for Mach bands, Chevreul’s illusion, and a variant of the Ehrenstein disk |
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2005 |
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Perception 34:209–210 Suppl. S (IF: 1.391) |
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D. Jayagopi; Bogdan Raducanu; D. Gatica-Perez |
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Characterizing conversational group dynamics using nonverbal behaviour |
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2009 |
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10th IEEE International Conference on Multimedia and Expo |
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370–373 |
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This paper addresses the novel problem of characterizing conversational group dynamics. It is well documented in social psychology that depending on the objectives a group, the dynamics are different. For example, a competitive meeting has a different objective from that of a collaborative meeting. We propose a method to characterize group dynamics based on the joint description of a group members' aggregated acoustical nonverbal behaviour to classify two meeting datasets (one being cooperative-type and the other being competitive-type). We use 4.5 hours of real behavioural multi-party data and show that our methodology can achieve a classification rate of upto 100%. |
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New York, USA |
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1945-7871 |
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978-1-4244-4290-4 |
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ICME |
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BCNPCL @ bcnpcl @ JRG2009 |
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1217 |
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Laura Igual; Santiago Segui; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
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Sparse Bayesian Feature Selection Applied to Intestinal Motility Analysis |
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2007 |
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XVI Congreso Argentino de Bioingenieria |
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467–470 |
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San Juan (Argentina) |
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SABI |
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MILAB;OR;MV |
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BCNPCL @ bcnpcl @ ISV2007b |
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896 |
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