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Author Ruth Aylett; Ginevra Castellano; Bogdan Raducanu; Ana Paiva; Marc Hanheide edit  url
doi  isbn
openurl 
  Title Long-term socially perceptive and interactive robot companions: challenges and future perspectives Type (down) Conference Article
  Year 2011 Publication 13th International Conference on Multimodal Interaction Abbreviated Journal  
  Volume Issue Pages 323-326  
  Keywords human-robot interaction, multimodal interaction, social robotics  
  Abstract This paper gives a brief overview of the challenges for multi-model perception and generation applied to robot companions located in human social environments. It reviews the current position in both perception and generation and the immediate technical challenges and goes on to consider the extra issues raised by embodiment and social context. Finally, it briefly discusses the impact of systems that must function continually over months rather than just for a few hours.  
  Address Alicante  
  Corporate Author Thesis  
  Publisher ACM Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4503-0641-6 Medium  
  Area Expedition Conference ICMI  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ ACR2011 Serial 1888  
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Author Fadi Dornaika; Alireza Bosaghzadeh; Bogdan Raducanu edit   pdf
openurl 
  Title LSDA Solution Schemes for Modelless 3D Head Pose Estimation Type (down) Conference Article
  Year 2012 Publication IEEE Workshop on the Applications of Computer Vision Abbreviated Journal  
  Volume Issue Pages 393-398  
  Keywords  
  Abstract  
  Address Breckenridge; USA;  
  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 WACV  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ DBR2012 Serial 1889  
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Author Bogdan Raducanu; Fadi Dornaika edit   pdf
doi  isbn
openurl 
  Title Appearance-based Face Recognition Using A Supervised Manifold Learning Framework Type (down) Conference Article
  Year 2012 Publication IEEE Workshop on the Applications of Computer Vision Abbreviated Journal  
  Volume Issue Pages 465-470  
  Keywords  
  Abstract Many natural image sets, depicting objects whose appearance is changing due to motion, pose or light variations, can be considered samples of a low-dimension nonlinear manifold embedded in the high-dimensional observation space (the space of all possible images). The main contribution of our work is represented by a Supervised Laplacian Eigemaps (S-LE) algorithm, which exploits the class label information for mapping the original data in the embedded space. Our proposed approach benefits from two important properties: i) it is discriminative, and ii) it adaptively selects the neighbors of a sample without using any predefined neighborhood size. Experiments were conducted on four face databases and the results demonstrate that the proposed algorithm significantly outperforms many linear and non-linear embedding techniques. Although we've focused on the face recognition problem, the proposed approach could also be extended to other category of objects characterized by large variance in their appearance.  
  Address Breckenridge; CO; USA  
  Corporate Author Thesis  
  Publisher IEEE Xplore Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1550-5790 ISBN 978-1-4673-0233-3 Medium  
  Area Expedition Conference WACV  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ RaD2012d Serial 1890  
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Author Antonio Hernandez; Carlos Primo; Sergio Escalera edit  doi
isbn  openurl
  Title Automatic user interaction correction via Multi-label Graph cuts Type (down) Conference Article
  Year 2011 Publication In ICCV 2011 1st IEEE International Workshop on Human Interaction in Computer Vision HICV Abbreviated Journal  
  Volume Issue Pages 1276-1281  
  Keywords  
  Abstract Most applications in image segmentation requires from user interaction in order to achieve accurate results. However, user wants to achieve the desired segmentation accuracy reducing effort of manual labelling. In this work, we extend standard multi-label α-expansion Graph Cut algorithm so that it analyzes the interaction of the user in order to modify the object model and improve final segmentation of objects. The approach is inspired in the fact that fast user interactions may introduce some pixel errors confusing object and background. Our results with different degrees of user interaction and input errors show high performance of the proposed approach on a multi-label human limb segmentation problem compared with classical α-expansion algorithm.  
  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 978-1-4673-0062-9 Medium  
  Area Expedition Conference HICV  
  Notes MILAB; HuPBA Approved no  
  Call Number Admin @ si @ HPE2011 Serial 1892  
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Author Miguel Reyes; Gabriel Dominguez; Sergio Escalera edit  url
doi  isbn
openurl 
  Title Feature Weighting in Dynamic Time Warping for Gesture Recognition in Depth Data Type (down) Conference Article
  Year 2011 Publication 1st IEEE Workshop on Consumer Depth Cameras for Computer Vision Abbreviated Journal  
  Volume Issue Pages 1182-1188  
  Keywords  
  Abstract We present a gesture recognition approach for depth video data based on a novel Feature Weighting approach within the Dynamic Time Warping framework. Depth features from human joints are compared through video sequences using Dynamic Time Warping, and weights are assigned to features based on inter-intra class gesture variability. Feature Weighting in Dynamic Time Warping is then applied for recognizing begin-end of gestures in data sequences. The obtained results recognizing several gestures in depth data show high performance compared with classical Dynamic Time Warping approach.  
  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 978-1-4673-0062-9 Medium  
  Area Expedition Conference CDC4CV  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ RDE2011 Serial 1893  
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Author Santiago Segui; Michal Drozdzal; Petia Radeva; Jordi Vitria edit   pdf
openurl 
  Title An Integrated Approach to Contextual Face Detection Type (down) Conference Article
  Year 2012 Publication 1st International Conference on Pattern Recognition Applications and Methods Abbreviated Journal  
  Volume Issue Pages 143-150  
  Keywords  
  Abstract Face detection is, in general, based on content-based detectors. Nevertheless, the face is a non-rigid object with well defined relations with respect to the human body parts. In this paper, we propose to take benefit of the context information in order to improve content-based face detections. We propose a novel framework for integrating multiple content- and context-based detectors in a discriminative way. Moreover, we develop an integrated scoring procedure that measures the ’faceness’ of each hypothesis and is used to discriminate the detection results. Our approach detects a higher rate of faces while minimizing the number of false detections, giving an average increase of more than 10% in average precision when comparing it to state-of-the art face detectors  
  Address Vilamoura, Algarve, Portugal  
  Corporate Author Thesis  
  Publisher Springer 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 ICPRAM  
  Notes MILAB; OR;MV Approved no  
  Call Number Admin @ si @ SDR2012 Serial 1895  
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Author Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate edit   pdf
doi  isbn
openurl 
  Title Error Analysis for Lucas-Kanade Based Schemes Type (down) Conference Article
  Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 7324 Issue I Pages 184-191  
  Keywords Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance  
  Abstract Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures.  
  Address Aveiro, Portugal  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin Heidelberg Place of Publication Editor  
  Language english Summary Language Original Title  
  Series Editor Campilho, Aurélio and Kamel, Mohamed Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-31294-6 Medium  
  Area Expedition Conference ICIAR  
  Notes IAM Approved no  
  Call Number IAM @ iam @ MGH2012a Serial 1899  
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Author Albert Andaluz; Francesc Carreras; Cristina Santa Marta;Debora Gil edit   pdf
url  openurl
  Title Myocardial torsion estimation with Tagged-MRI in the OsiriX platform Type (down) Conference Article
  Year 2012 Publication ISBI Workshop on Open Source Medical Image Analysis software Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Myocardial torsion (MT) plays a crucial role in the assessment of the functionality of the
left ventricle. For this purpose, the IAM group at the CVC has developed the Harmonic Phase Flow (HPF) plugin for the Osirix DICOM platform . We have validated its funcionalty on sequences acquired using different protocols and including healthy and pathological cases. Results show similar torsion trends for SPAMM acquisitions, with pathological cases introducing expected deviations from the ground truth. Finally, we provide the plugin free of charge at http://iam.cvc.uab.es
 
  Address Barcelona, Spain  
  Corporate Author Thesis  
  Publisher IEEE Place of Publication Editor Wiro Niessen (Erasmus MC) and Marc Modat (UCL)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ISBI  
  Notes IAM Approved no  
  Call Number IAM @ iam @ ACS2012 Serial 1900  
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Author Patricia Marquez; Debora Gil; Aura Hernandez-Sabate edit   pdf
url  doi
openurl 
  Title Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality Type (down) Conference Article
  Year 2013 Publication ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars Abbreviated Journal  
  Volume Issue Pages 624-631  
  Keywords  
  Abstract Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field.  
  Address Sydney; Australia; December 2013  
  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 CVTT:E2M  
  Notes IAM; ADAS; 600.044; 600.057; 601.145 Approved no  
  Call Number Admin @ si @ MGH2013b Serial 2351  
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Author Francesco Ciompi; Rui Hua; Simone Balocco; Marina Alberti; Oriol Pujol; Carles Caus; Josepa Mauri; Petia Radeva edit  doi
isbn  openurl
  Title Learning to Detect Stent Struts in Intravascular Ultrasound Type (down) Conference Article
  Year 2013 Publication 6th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 7887 Issue Pages 575-583  
  Keywords  
  Abstract In this paper we tackle the automatic detection of struts elements (metallic braces of a stent device) in Intravascular Ultrasound (IVUS) sequences. The proposed method is based on context-aware classification of IVUS images, where we use Multi-Class Multi-Scale Stacked Sequential Learning (M2SSL). Additionally, we introduce a novel technique to reduce the amount of required contextual features. The comparison with binary and multi-class learning is also performed, using a dataset of IVUS images with struts manually annotated by an expert. The best performing configuration reaches a F-measure F = 63.97% .  
  Address Madeira; Portugal; June 2013  
  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 978-3-642-38627-5 Medium  
  Area Expedition Conference IbPRIA  
  Notes MILAB; HuPBA; 605.203; 600.046 Approved no  
  Call Number Admin @ si @ CHB2013 Serial 2349  
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Author Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados edit   pdf
openurl 
  Title Classification of Administrative Document Images by Logo Identification Type (down) Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier's graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents.  
  Address Bethlehem; PA; USA; August 2013  
  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 GREC  
  Notes DAG; 600.056; 600.045; 605.203 Approved no  
  Call Number Admin @ si @ Serial 2348  
Permanent link to this record
 

 
Author Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados edit   pdf
openurl 
  Title Spotting Graphical Symbols in Camera-Acquired Documents in Real Time Type (down) Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time.  
  Address Bethlehem; PA; USA; August 2013  
  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 GREC  
  Notes DAG; 600.045; 600.055; 600.061; 602.101 Approved no  
  Call Number Admin @ si @ RKL2013 Serial 2347  
Permanent link to this record
 

 
Author Marçal Rusiñol; T.Benkhelfallah; V. Poulain d'Andecy edit   pdf
doi  openurl
  Title Field Extraction from Administrative Documents by Incremental Structural Templates Type (down) Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1100 - 1104  
  Keywords  
  Abstract In this paper we present an incremental framework aimed at extracting field information from administrative document images in the context of a Digital Mail-room scenario. Given a single training sample in which the user has marked which fields have to be extracted from a particular document class, a document model representing structural relationships among words is built. This model is incrementally refined as the system processes more and more documents from the same class. A reformulation of the tf-idf statistic scheme allows to adjust the importance weights of the structural relationships among words. We report in the experimental section our results obtained with a large dataset of real invoices.  
  Address Washington; USA; August 2013  
  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 1520-5363 ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; 600.56; 600.045; 605.203; 602.101 Approved no  
  Call Number Admin @ si @ RBP2013 Serial 2346  
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Author Albert Gordo; Marçal Rusiñol; Dimosthenis Karatzas; Andrew Bagdanov edit   pdf
doi  openurl
  Title Document Classification and Page Stream Segmentation for Digital Mailroom Applications Type (down) Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 621-625  
  Keywords  
  Abstract In this paper we present a method for the segmentation of continuous page streams into multipage documents and the simultaneous classification of the resulting documents. We first present an approach to combine the multiple pages of a document into a single feature vector that represents the whole document. Despite its simplicity and low computational cost, the proposed representation yields results comparable to more complex methods in multipage document classification tasks. We then exploit this representation in the context of page stream segmentation. The most plausible segmentation of a page stream into a sequence of multipage documents is obtained by optimizing a statistical model that represents the probability of each segmented multipage document belonging to a particular class. Experimental results are reported on a large sample of real administrative multipage documents.  
  Address Washington; USA; August 2013  
  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 1520-5363 ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; 600.056; 602.101 Approved no  
  Call Number Admin @ si @ GRK2013c Serial 2345  
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Author L. Rothacker; Marçal Rusiñol; G.A. Fink edit   pdf
doi  openurl
  Title Bag-of-Features HMMs for segmentation-free word spotting in handwritten documents Type (down) Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1305 - 1309  
  Keywords  
  Abstract Recent HMM-based approaches to handwritten word spotting require large amounts of learning samples and mostly rely on a prior segmentation of the document. We propose to use Bag-of-Features HMMs in a patch-based segmentation-free framework that are estimated by a single sample. Bag-of-Features HMMs use statistics of local image feature representatives. Therefore they can be considered as a variant of discrete HMMs allowing to model the observation of a number of features at a point in time. The discrete nature enables us to estimate a query model with only a single example of the query provided by the user. This makes our method very flexible with respect to the availability of training data. Furthermore, we are able to outperform state-of-the-art results on the George Washington dataset.  
  Address Washington; USA; August 2013  
  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 1520-5363 ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number Admin @ si @ RRF2013 Serial 2344  
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