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Author Joan Arnedo-Moreno; Agata Lapedriza edit  openurl
  Title Visualizing key authenticity: turning your face into your public key Type Conference Article
  Year 2010 Publication 6th China International Conference on Information Security and Cryptology Abbreviated Journal  
  Volume Issue Pages 605-618  
  Keywords  
  Abstract Biometric information has become a technology complementary to cryptography, allowing to conveniently manage cryptographic data. Two important needs are ful lled: rst of all, making such data always readily available, and additionally, making its legitimate owner easily identi able. In this work we propose a signature system which integrates face recognition biometrics with and identity-based signature scheme, so the user's face e ectively becomes his public key and system ID. Thus, other users may verify messages using photos of the claimed sender, providing a reasonable trade-o between system security and usability, as well as a much more straightforward public key authenticity and distribution process.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference Inscrypt  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ ArL2010c Serial 2149  
Permanent link to this record
 

 
Author Cesar Isaza; Joaquin Salas; Bogdan Raducanu edit  doi
openurl 
  Title Evaluation of Intrinsic Image Algorithms to Detect the Shadows Cast by Static Objects Outdoors Type Journal Article
  Year 2012 Publication Sensors Abbreviated Journal SENS  
  Volume 12 Issue 10 Pages 13333-13348  
  Keywords  
  Abstract In some automatic scene analysis applications, the presence of shadows becomes a nuisance that is necessary to deal with. As a consequence, a preliminary stage in many computer vision algorithms is to attenuate their effect. In this paper, we focus our attention on the detection of shadows cast by static objects outdoors, as the scene is viewed for extended periods of time (days, weeks) from a fixed camera and considering daylight intervals where the main source of light is the sun. In this context, we report two contributions. First, we introduce the use of synthetic images for which ground truth can be generated automatically, avoiding the tedious effort of manual annotation. Secondly, we report a novel application of the intrinsic image concept to the automatic detection of shadows cast by static objects in outdoors. We make both a quantitative and a qualitative evaluation of several algorithms based on this image representation. For the quantitative evaluation, we used the synthetic data set, while for the qualitative evaluation we used both data sets. Our experimental results show that the evaluated methods can partially solve the problem of shadow detection.  
  Address  
  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 ISBN Medium  
  Area Expedition Conference  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ ISR2012b Serial 2173  
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Author Fadi Dornaika; A.Assoum; Bogdan Raducanu edit   pdf
doi  isbn
openurl 
  Title Automatic Dimensionality Estimation for Manifold Learning through Optimal Feature Selection Type Conference Article
  Year 2012 Publication Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop Abbreviated Journal  
  Volume 7626 Issue Pages 575-583  
  Keywords  
  Abstract A very important aspect in manifold learning is represented by automatic estimation of the intrinsic dimensionality. Unfortunately, this problem has received few attention in the literature of manifold learning. In this paper, we argue that feature selection paradigm can be used to the problem of automatic dimensionality estimation. Besides this, it also leads to improved recognition rates. Our approach for optimal feature selection is based on a Genetic Algorithm. As a case study for manifold learning, we have considered Laplacian Eigenmaps (LE) and Locally Linear Embedding (LLE). The effectiveness of the proposed framework was tested on the face recognition problem. Extensive experiments carried out on ORL, UMIST, Yale, and Extended Yale face data sets confirmed our hypothesis.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-34165-6 Medium  
  Area Expedition Conference SSPR&SPR  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ DAR2012 Serial 2174  
Permanent link to this record
 

 
Author Bogdan Raducanu; Fadi Dornaika edit   pdf
doi  isbn
openurl 
  Title Out-of-Sample Embedding by Sparse Representation Type Conference Article
  Year 2012 Publication Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop Abbreviated Journal  
  Volume 7626 Issue Pages 336-344  
  Keywords  
  Abstract A critical aspect of non-linear dimensionality reduction techniques is represented by the construction of the adjacency graph. The difficulty resides in finding the optimal parameters, a process which, in general, is heuristically driven. Recently, sparse representation has been proposed as a non-parametric solution to overcome this problem. In this paper, we demonstrate that this approach not only serves for the graph construction, but also represents an efficient and accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. Experimental results conducted on some challenging datasets confirmed the robustness of our approach and its superiority when compared to existing techniques.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-34165-6 Medium  
  Area Expedition Conference SSPR&SPR  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ RaD2012c Serial 2175  
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Author Bogdan Raducanu; Fadi Dornaika edit   pdf
doi  isbn
openurl 
  Title Pose-Invariant Face Recognition in Videos for Human-Machine Interaction Type Conference Article
  Year 2012 Publication 12th European Conference on Computer Vision Abbreviated Journal  
  Volume 7584 Issue Pages 566.575  
  Keywords  
  Abstract Human-machine interaction is a hot topic nowadays in the communities of computer vision and robotics. In this context, face recognition algorithms (used as primary cue for a person’s identity assessment) work well under controlled conditions but degrade significantly when tested in real-world environments. This is mostly due to the difficulty of simultaneously handling variations in illumination, pose, and occlusions. In this paper, we propose a novel approach for robust pose-invariant face recognition for human-robot interaction based on the real-time fitting of a 3D deformable model to input images taken from video sequences. More concrete, our approach generates a rectified face image irrespective with the actual head-pose orientation. Experimental results performed on Honda video database, using several manifold learning techniques, show a distinct advantage of the proposed method over the standard 2D appearance-based snapshot approach.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-33867-0 Medium  
  Area Expedition Conference ECCVW  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ RaD2012e Serial 2182  
Permanent link to this record
 

 
Author Fadi Dornaika; Bogdan Raducanu edit   pdf
openurl 
  Title Analysis and Recognition of Facial Expressions in Videos Using Facial Shape Deformation Type Book Chapter
  Year 2012 Publication Facial Expressions: Dynamic Patterns, Impairments and Social Perceptions Abbreviated Journal  
  Volume Issue Pages 157-178  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher NOVA Publishers Place of Publication Editor S.E. Carter  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ DoR2012 Serial 2183  
Permanent link to this record
 

 
Author Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu edit   pdf
openurl 
  Title Estado del Arte en Sistemas de Vision Artificial para Personas Invidentes Type Journal
  Year 2013 Publication Komputer Sapiens Abbreviated Journal KS  
  Volume 1 Issue Pages 20-25  
  Keywords  
  Abstract  
  Address  
  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 ISBN Medium  
  Area Expedition Conference  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ TSR2013 Serial 2231  
Permanent link to this record
 

 
Author David Masip; Michael S. North ; Alexander Todorov; Daniel N. Osherson edit   pdf
doi  openurl
  Title Automated Prediction of Preferences Using Facial Expressions Type Journal Article
  Year 2014 Publication PloS one Abbreviated Journal Plos  
  Volume 9 Issue 2 Pages e87434  
  Keywords  
  Abstract We introduce a computer vision problem from social cognition, namely, the automated detection of attitudes from a person's spontaneous facial expressions. To illustrate the challenges, we introduce two simple algorithms designed to predict observers’ preferences between images (e.g., of celebrities) based on covert videos of the observers’ faces. The two algorithms are almost as accurate as human judges performing the same task but nonetheless far from perfect. Our approach is to locate facial landmarks, then predict preference on the basis of their temporal dynamics. The database contains 768 videos involving four different kinds of preferences. We make it publically available.  
  Address  
  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 ISBN Medium  
  Area Expedition Conference  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ MNT2014 Serial 2453  
Permanent link to this record
 

 
Author Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu edit  doi
isbn  openurl
  Title Robust Head Gestures Recognition for Assistive Technology Type Book Chapter
  Year 2014 Publication Pattern Recognition Abbreviated Journal  
  Volume 8495 Issue Pages 152-161  
  Keywords  
  Abstract This paper presents a system capable of recognizing six head gestures: nodding, shaking, turning right, turning left, looking up, and looking down. The main difference of our system compared to other methods is that the Hidden Markov Models presented in this paper, are fully connected and consider all possible states in any given order, providing the following advantages to the system: (1) allows unconstrained movement of the head and (2) it can be easily integrated into a wearable device (e.g. glasses, neck-hung devices), in which case it can robustly recognize gestures in the presence of ego-motion. Experimental results show that this approach outperforms common methods that use restricted HMMs for each gesture.  
  Address  
  Corporate Author Thesis  
  Publisher Springer International Publishing Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-319-07490-0 Medium  
  Area Expedition Conference  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ TSR2014b Serial 2505  
Permanent link to this record
 

 
Author Manuel Graña; Bogdan Raducanu edit  doi
openurl 
  Title Special Issue on Bioinspired and knowledge based techniques and applications Type Journal Article
  Year 2015 Publication Neurocomputing Abbreviated Journal NEUCOM  
  Volume Issue Pages 1-3  
  Keywords  
  Abstract  
  Address  
  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 ISBN Medium  
  Area Expedition Conference  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ GrR2015 Serial 2598  
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Author Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika edit  openurl
  Title Facial Expression Recognition based on Multi-view Observations with Application to Social Robotics Type Conference Article
  Year 2014 Publication 1st Workshop on Computer Vision for Affective Computing Abbreviated Journal  
  Volume Issue Pages 1-8  
  Keywords  
  Abstract Human-robot interaction is a hot topic nowadays in the social robotics community. One crucial aspect is represented by the affective communication which comes encoded through the facial expressions. In this paper, we propose a novel approach for facial expression recognition, which exploits an efficient and adaptive graph-based label propagation (semi-supervised mode) in a multi-observation framework. The facial features are extracted using an appearance-based 3D face tracker, view- and texture independent. Our method has been extensively tested on the CMU dataset, and has been conveniently compared with other methods for graph construction. With the proposed approach, we developed an application for an AIBO robot, in which it mirrors the recognized facial
expression.
 
  Address Singapore; November 2014  
  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 ISBN Medium  
  Area Expedition Conference ACCV  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ RBD2014 Serial 2599  
Permanent link to this record
 

 
Author R. Clariso; David Masip; A. Rius edit  url
openurl 
  Title Student projects empowering mobile learning in higher education Type Journal
  Year 2014 Publication Revista de Universidad y Sociedad del Conocimiento Abbreviated Journal RUSC  
  Volume 11 Issue Pages 192-207  
  Keywords  
  Abstract  
  Address  
  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 1698-580X ISBN Medium  
  Area Expedition Conference  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ CMR2014 Serial 2619  
Permanent link to this record
 

 
Author B. Zhou; Agata Lapedriza; J. Xiao; A. Torralba; A. Oliva edit  url
openurl 
  Title Learning Deep Features for Scene Recognition using Places Database Type Conference Article
  Year 2014 Publication 28th Annual Conference on Neural Information Processing Systems Abbreviated Journal  
  Volume Issue Pages 487-495  
  Keywords  
  Abstract  
  Address Montreal; Canada; December 2014  
  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 ISBN Medium  
  Area Expedition Conference NIPS  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ ZLX2014 Serial 2621  
Permanent link to this record
 

 
Author Agata Lapedriza; David Masip; D.Sanchez edit  doi
isbn  openurl
  Title Emotions Classification using Facial Action Units Recognition Type Conference Article
  Year 2014 Publication 17th International Conference of the Catalan Association for Artificial Intelligence Abbreviated Journal  
  Volume 269 Issue Pages 55-64  
  Keywords  
  Abstract In this work we build a system for automatic emotion classification from image sequences. We analyze subtle changes in facial expressions by detecting a subset of 12 representative facial action units (AUs). Then, we classify emotions based on the output of these AUs classifiers, i.e. the presence/absence of AUs. We base the AUs classification upon a set of spatio-temporal geometric and appearance features for facial representation, fusing them within the emotion classifier. A decision tree is trained for emotion classifying, making the resulting model easy to interpret by capturing the combination of AUs activation that lead to a particular emotion. For Cohn-Kanade database, the proposed system classifies 7 emotions with a mean accuracy of near 90%, attaining a similar recognition accuracy in comparison with non-interpretable models that are not based in AUs detection.  
  Address  
  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 ISBN 978-1-61499-451-0 Medium  
  Area Expedition Conference CCIA  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ LMS2014 Serial 2622  
Permanent link to this record
 

 
Author Fadi Dornaika; Bogdan Raducanu; Alireza Bosaghzadeh edit  openurl
  Title Facial expression recognition based on multi observations with application to social robotics Type Book Chapter
  Year 2015 Publication Emotional and Facial Expressions: Recognition, Developmental Differences and Social Importance Abbreviated Journal  
  Volume Issue Pages 153-166  
  Keywords  
  Abstract Human-robot interaction is a hot topic nowadays in the social robotics
community. One crucial aspect is represented by the affective communication
which comes encoded through the facial expressions. In this chapter, we propose a novel approach for facial expression recognition, which exploits an efficient and adaptive graph-based label propagation (semi-supervised mode) in a multi-observation framework. The facial features are extracted using an appearance-based 3D face tracker, viewand texture independent. Our method has been extensively tested on the CMU dataset, and has been conveniently compared with other methods for graph construction. With the proposed approach, we developed an application for an AIBO robot, in which it mirrors the recognized facial
expression.
 
  Address  
  Corporate Author Thesis  
  Publisher Nova Science publishers Place of Publication Editor Bruce Flores  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes (down) OR;MV Approved no  
  Call Number Admin @ si @ DRB2015 Serial 2720  
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