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Author |
Patricia Marquez; H. Kause; A. Fuster; Aura Hernandez-Sabate; L. Florack; Debora Gil; Hans van Assen |
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Title  |
Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging |
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Conference Article |
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Year |
2014 |
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17th International Conference on Medical Image Computing and Computer Assisted Intervention |
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Volume |
8896 |
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231-238 |
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Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging |
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Abstract |
Changes in cardiac deformation patterns are correlated with cardiac pathologies. Deformation can be extracted from tagging Magnetic Resonance Imaging (tMRI) using Optical Flow (OF) techniques. For applications of OF in a clinical setting it is important to assess to what extent the performance of a particular OF method is stable across di erent clinical acquisition artifacts. This paper presents a statistical validation framework, based on ANOVA, to assess the motion and appearance factors that have the largest in uence on OF accuracy drop.
In order to validate this framework, we created a database of simulated tMRI data including the most common artifacts of MRI and test three di erent OF methods, including HARP. |
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Boston; USA; September 2014 |
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Springer International Publishing |
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0302-9743 |
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978-3-319-14677-5 |
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STACOM |
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IAM; ADAS; 600.060; 601.145; 600.076; 600.075 |
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Admin @ si @ MKF2014 |
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2495 |
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Author |
Josep M. Gonfaus; Marco Pedersoli; Jordi Gonzalez; Andrea Vedaldi; Xavier Roca |
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Title |
Factorized appearances for object detection |
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Journal Article |
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Year |
2015 |
Publication |
Computer Vision and Image Understanding |
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CVIU |
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138 |
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92–101 |
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Object recognition; Deformable part models; Learning and sharing parts; Discovering discriminative parts |
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Deformable object models capture variations in an object’s appearance that can be represented as image deformations. Other effects such as out-of-plane rotations, three-dimensional articulations, and self-occlusions are often captured by considering mixture of deformable models, one per object aspect. A more scalable approach is representing instead the variations at the level of the object parts, applying the concept of a mixture locally. Combining a few part variations can in fact cheaply generate a large number of global appearances.
A limited version of this idea was proposed by Yang and Ramanan [1], for human pose dectection. In this paper we apply it to the task of generic object category detection and extend it in several ways. First, we propose a model for the relationship between part appearances more general than the tree of Yang and Ramanan [1], which is more suitable for generic categories. Second, we treat part locations as well as their appearance as latent variables so that training does not need part annotations but only the object bounding boxes. Third, we modify the weakly-supervised learning of Felzenszwalb et al. and Girshick et al. [2], [3] to handle a significantly more complex latent structure.
Our model is evaluated on standard object detection benchmarks and is found to improve over existing approaches, yielding state-of-the-art results for several object categories. |
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ISE; 600.063; 600.078 |
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Admin @ si @ GPG2015 |
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2705 |
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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
Factorization with Missing and Noisy Data |
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Conference Article |
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Year |
2006 |
Publication |
6th International Conference on Computational Science |
Abbreviated Journal |
ICCS´06 |
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LNCS 3991 |
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555–562 |
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Reading (United Kingdom) |
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ADAS |
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ADAS @ adas @ JSL2006b |
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653 |
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Author |
Petia Radeva; Enric Marti |
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Title |
Facial Features Segmentation by Model-Based Snakes. |
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Miscellaneous |
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1995 |
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Trobada de Joves Investigadors, IIIA. |
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Bellaterra (Barcelona), Spain |
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MILAB; IAM |
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BCNPCL @ bcnpcl @ RaM1995a |
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130 |
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Author |
Petia Radeva; Enric Marti |
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Title |
Facial Features Segmentation by Model-Based Snakes |
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Conference Article |
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1995 |
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International Conference on Computing Analysis and Image Processing |
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Deformable models have recently been accepted as a standard technique to segment different features in facial images. Despite they give a good approximation of the salient features in a facial image, the resulting shapes of the segmentation process seem somewhat artificial with respect to the natural feature shapes. In this paper we show that active contour models (in particular, rubber snakes) give more close and natural representation of the detected feature shape. Besides, using snakes for facial segmentation frees us from the problem of determination of the numerous weigths of deformable models. Another advantage of rubber snakes is their reduced computational cost. Our experiments using rubber snakes for segmentation of facial snapshots have shown a significant improvement compared to deformable models. |
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Bellaterra (Barcelona), Spain |
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MILAB;IAM |
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IAM @ iam @ RAM1995a |
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1633 |
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Author |
Fadi Dornaika; Abdelmalik Moujahid; Bogdan Raducanu |
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Title |
Facial expression recognition using tracked facial actions: Classifier performance analysis |
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Journal Article |
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Year |
2013 |
Publication |
Engineering Applications of Artificial Intelligence |
Abbreviated Journal |
EAAI |
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26 |
Issue |
1 |
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467-477 |
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Visual face tracking; 3D deformable models; Facial actions; Dynamic facial expression recognition; Human–computer interaction |
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In this paper, we address the analysis and recognition of facial expressions in continuous videos. More precisely, we study classifiers performance that exploit head pose independent temporal facial action parameters. These are provided by an appearance-based 3D face tracker that simultaneously provides the 3D head pose and facial actions. The use of such tracker makes the recognition pose- and texture-independent. Two different schemes are studied. The first scheme adopts a dynamic time warping technique for recognizing expressions where training data are given by temporal signatures associated with different universal facial expressions. The second scheme models temporal signatures associated with facial actions with fixed length feature vectors (observations), and uses some machine learning algorithms in order to recognize the displayed expression. Experiments quantified the performance of different schemes. These were carried out on CMU video sequences and home-made video sequences. The results show that the use of dimension reduction techniques on the extracted time series can improve the classification performance. Moreover, these experiments show that the best recognition rate can be above 90%. |
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Elsevier |
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OR; 600.046;MV |
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Admin @ si @ DMR2013 |
Serial |
2185 |
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Author |
Fadi Dornaika; Franck Davoine |
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Title |
Facial expression recognition using auto-regressive models |
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Miscellaneous |
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2006 |
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18th International Conference on Pattern Recognition (ICPR´06), ISBN: 0–7695–2521–0, 4: 520–523 |
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Hong Kong |
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no |
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Admin @ si @ DoD2006a |
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734 |
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Author |
Fadi Dornaika; Franck Davoine |
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Title |
Facial expression recognition in continuous videos using dynamic programming |
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Miscellaneous |
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2005 |
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IEEE Int. Conference on Image Processing |
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Genova (Italy) |
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Admin @ si @ DoD2005a |
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597 |
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Author |
Fadi Dornaika; Bogdan Raducanu |
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Title |
Facial Expression Recognition for HCI Applications |
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2008 |
Publication |
Encyclopedia of Artificial Intelligence |
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II |
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625–631 |
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IGI–Global Publisher |
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Rabuñal |
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OR;MV |
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BCNPCL @ bcnpcl @ DoR2008c |
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1034 |
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Author |
Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika |
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Title |
Facial Expression Recognition based on Multi-view Observations with Application to Social Robotics |
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Conference Article |
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2014 |
Publication |
1st Workshop on Computer Vision for Affective Computing |
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1-8 |
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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. |
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Singapore; November 2014 |
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ACCV |
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LAMP; |
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Admin @ si @ RBD2014 |
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2599 |
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Author |
Fadi Dornaika; Bogdan Raducanu; Alireza Bosaghzadeh |
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Facial expression recognition based on multi observations with application to social robotics |
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Book Chapter |
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2015 |
Publication |
Emotional and Facial Expressions: Recognition, Developmental Differences and Social Importance |
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153-166 |
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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. |
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Nova Science publishers |
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Bruce Flores |
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LAMP; |
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Admin @ si @ DRB2015 |
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2720 |
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Author |
Zhong Jin; Franck Davoine; Zhen Lou |
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Facial expression analysis by using KPCA |
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2003 |
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IEEE International Conference on Robotics, Intelligent Systems and Signal Processing (IEEE RISSP 2003), pp736–741 |
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Changsha, Hunan, China |
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Admin @ si @ JDL2003 |
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431 |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Face-to-face social activity detection using data collected with a wearable device |
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Conference Article |
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2009 |
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4th Iberian Conference on Pattern Recognition and Image Analysis |
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5524 |
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56–63 |
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In this work the feasibility of building a socially aware badge that learns from user activities is explored. A wearable multisensor device has been prototyped for collecting data about user movements and photos of the environment where the user acts. Using motion data, speaking and other activities have been classified. Images have been analysed in order to complement motion data and help for the detection of social behaviours. A face detector and an activity classifier are both used for detecting if users have a social activity in the time they worn the device. Good results encourage the improvement of the system at both hardware and software level |
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Póvoa de Varzim, Portugal |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-02171-8 |
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IbPRIA |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ CPR2009b |
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1206 |
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Author |
Agata Lapedriza; David Masip; Jordi Vitria |
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Face Verification using External Features |
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Miscellaneous |
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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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OR;MV |
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no |
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BCNPCL @ bcnpcl @ LMV2006a |
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707 |
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David Masip; Agata Lapedriza; Jordi Vitria |
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Face Verification Sharing Knowledge from Different Subjects |
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2007 |
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2nd International Conference on Computer Vision Theory and Applications |
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2 |
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268–289 |
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Address |
Barcelona (Spain) |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
VISAPP´07 |
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Notes |
OR; MV |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ MLV2007a |
Serial |
995 |
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