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Author Arya Farkhondeh; Cristina Palmero; Simone Scardapane; Sergio Escalera edit   pdf
openurl 
  Title Towards Self-Supervised Gaze Estimation Type Miscellaneous
  Year 2022 Publication Arxiv Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Recent joint embedding-based self-supervised methods have surpassed standard supervised approaches on various image recognition tasks such as image classification. These self-supervised methods aim at maximizing agreement between features extracted from two differently transformed views of the same image, which results in learning an invariant representation with respect to appearance and geometric image transformations. However, the effectiveness of these approaches remains unclear in the context of gaze estimation, a structured regression task that requires equivariance under geometric transformations (e.g., rotations, horizontal flip). In this work, we propose SwAT, an equivariant version of the online clustering-based self-supervised approach SwAV, to learn more informative representations for gaze estimation. We demonstrate that SwAT, with ResNet-50 and supported with uncurated unlabeled face images, outperforms state-of-the-art gaze estimation methods and supervised baselines in various experiments. In particular, we achieve up to 57% and 25% improvements in cross-dataset and within-dataset evaluation tasks on existing benchmarks (ETH-XGaze, Gaze360, and MPIIFaceGaze).  
  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 HUPBA; no menciona Approved no  
  Call Number (down) Admin @ si @ FPS2022 Serial 3822  
Permanent link to this record
 

 
Author Alicia Fornes; Gemma Sanchez edit  doi
isbn  openurl
  Title Analysis and Recognition of Music Scores Type Book Chapter
  Year 2014 Publication Handbook of Document Image Processing and Recognition Abbreviated Journal  
  Volume E Issue Pages 749-774  
  Keywords  
  Abstract The analysis and recognition of music scores has attracted the interest of researchers for decades. Optical Music Recognition (OMR) is a classical research field of Document Image Analysis and Recognition (DIAR), whose aim is to extract information from music scores. Music scores contain both graphical and textual information, and for this reason, techniques are closely related to graphics recognition and text recognition. Since music scores use a particular diagrammatic notation that follow the rules of music theory, many approaches make use of context information to guide the recognition and solve ambiguities. This chapter overviews the main Optical Music Recognition (OMR) approaches. Firstly, the different methods are grouped according to the OMR stages, namely, staff removal, music symbol recognition, and syntactical analysis. Secondly, specific approaches for old and handwritten music scores are reviewed. Finally, online approaches and commercial systems are also commented.  
  Address  
  Corporate Author Thesis  
  Publisher Springer London Place of Publication Editor D. Doermann; K. Tombre  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-0-85729-860-7 Medium  
  Area Expedition Conference  
  Notes DAG; ADAS; 600.076; 600.077 Approved no  
  Call Number (down) Admin @ si @ FoS2014 Serial 2484  
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Author Alicia Fornes; Bart Lamiroy edit  url
isbn  openurl
  Title Graphics Recognition, Current Trends and Evolutions Type Book Whole
  Year 2018 Publication Graphics Recognition, Current Trends and Evolutions Abbreviated Journal  
  Volume 11009 Issue Pages  
  Keywords  
  Abstract This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Workshop on Graphics Recognition, GREC 2017, held in Kyoto, Japan, in November 2017.
The 10 revised full papers presented were carefully reviewed and selected from 14 initial submissions. They contain both classical and emerging topics of graphics rcognition, namely analysis and detection of diagrams, search and classification, optical music recognition, interpretation of engineering drawings and maps.
 
  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 ISBN 978-3-030-02283-9 Medium  
  Area Expedition Conference  
  Notes DAG; 600.121 Approved no  
  Call Number (down) Admin @ si @ FoL2018 Serial 3171  
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Author Alicia Fornes; Xavier Otazu; Josep Llados edit   pdf
doi  openurl
  Title Show through cancellation and image enhancement by multiresolution contrast processing Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 200-204  
  Keywords  
  Abstract Historical documents suffer from different types of degradation and noise such as background variation, uneven illumination or dark spots. In case of double-sided documents, another common problem is that the back side of the document usually interferes with the front side because of the transparency of the document or ink bleeding. This effect is called the show through phenomenon. Many methods are developed to solve these problems, and in the case of show-through, by scanning and matching both the front and back sides of the document. In contrast, our approach is designed to use only one side of the scanned document. We hypothesize that show-trough are low contrast components, while foreground components are high contrast ones. A Multiresolution Contrast (MC) decomposition is presented in order to estimate the contrast of features at different spatial scales. We cancel the show-through phenomenon by thresholding these low contrast components. This decomposition is also able to enhance the image removing shadowed areas by weighting spatial scales. Results show that the enhanced images improve the readability of the documents, allowing scholars both to recover unreadable words and to solve ambiguities.  
  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; 602.006; 600.045; 600.061; 600.052;CIC Approved no  
  Call Number (down) Admin @ si @ FOL2013 Serial 2241  
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Author Josep Famadas; Meysam Madadi; Cristina Palmero; Sergio Escalera edit   pdf
url  openurl
  Title Generative Video Face Reenactment by AUs and Gaze Regularization Type Conference Article
  Year 2020 Publication 15th IEEE International Conference on Automatic Face and Gesture Recognition Abbreviated Journal  
  Volume Issue Pages 444-451  
  Keywords  
  Abstract In this work, we propose an encoder-decoder-like architecture to perform face reenactment in image sequences. Our goal is to transfer the training subject identity to a given test subject. We regularize face reenactment by facial action unit intensity and 3D gaze vector regression. This way, we enforce the network to transfer subtle facial expressions and eye dynamics, providing a more lifelike result. The proposed encoder-decoder receives as input the previous sequence frame stacked to the current frame image of facial landmarks. Thus, the generated frames benefit from appearance and geometry, while keeping temporal coherence for the generated sequence. At test stage, a new target subject with the facial performance of the source subject and the appearance of the training subject is reenacted. Principal component analysis is applied to project the test subject geometry to the closest training subject geometry before reenactment. Evaluation of our proposal shows faster convergence, and more accurate and realistic results in comparison to other architectures without action units and gaze regularization.  
  Address Virtual; November 2020  
  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 FG  
  Notes HUPBA Approved no  
  Call Number (down) Admin @ si @ FMP2020 Serial 3517  
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Author Alicia Fornes; Beata Megyesi; Joan Mas edit   pdf
openurl 
  Title Transcription of Encoded Manuscripts with Image Processing Techniques Type Conference Article
  Year 2017 Publication Digital Humanities Conference Abbreviated Journal  
  Volume Issue Pages 441-443  
  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 DH  
  Notes DAG; 600.097; 600.121 Approved no  
  Call Number (down) Admin @ si @ FMM2017 Serial 3061  
Permanent link to this record
 

 
Author David Fernandez; R.Manmatha; Josep Llados; Alicia Fornes edit   pdf
doi  isbn
openurl 
  Title Sequential Word Spotting in Historical Handwritten Documents Type Conference Article
  Year 2014 Publication 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal  
  Volume Issue Pages 101 - 105  
  Keywords  
  Abstract In this work we present a handwritten word spotting approach that takes advantage of the a priori known order of appearance of the query words. Given an ordered sequence of query word instances, the proposed approach performs a
sequence alignment with the words in the target collection. Although the alignment is quite sparse, i.e. the number of words in the database is higher than the query set, the improvement in the overall performance is sensitively higher than isolated word spotting. As application dataset, we use a collection of handwritten marriage licenses taking advantage of the ordered
index pages of family names.
 
  Address Tours; Francia; April 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 978-1-4799-3243-6 Medium  
  Area Expedition Conference DAS  
  Notes DAG; 600.061; 600.056; 602.006; 600.077 Approved no  
  Call Number (down) Admin @ si @ FML2014 Serial 2462  
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Author David Fernandez; Simone Marinai; Josep Llados; Alicia Fornes edit   pdf
doi  isbn
openurl 
  Title Contextual Word Spotting in Historical Manuscripts using Markov Logic Networks Type Conference Article
  Year 2013 Publication 2nd International Workshop on Historical Document Imaging and Processing Abbreviated Journal  
  Volume Issue Pages 36-43  
  Keywords  
  Abstract Natural languages can often be modelled by suitable grammars whose knowledge can improve the word spotting results. The implicit contextual information is even more useful when dealing with information that is intrinsically described as one collection of records. In this paper, we present one approach to word spotting which uses the contextual information of records to improve the results. The method relies on Markov Logic Networks to probabilistically model the relational organization of handwritten records. The performance has been evaluated on the Barcelona Marriages Dataset that contains structured handwritten records that summarize marriage information.  
  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 ISBN 978-1-4503-2115-0 Medium  
  Area Expedition Conference HIP  
  Notes DAG; 600.056; 600.045; 600.061; 602.006 Approved no  
  Call Number (down) Admin @ si @ FML2013 Serial 2308  
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Author Hao Fang; Ajian Liu; Jun Wan; Sergio Escalera; Chenxu Zhao; Xu Zhang; Stan Z Li; Zhen Lei edit   pdf
url  openurl
  Title Surveillance Face Anti-spoofing Type Journal Article
  Year 2024 Publication IEEE Transactions on Information Forensics and Security Abbreviated Journal TIFS  
  Volume 19 Issue Pages 1535-1546  
  Keywords  
  Abstract Face Anti-spoofing (FAS) is essential to secure face recognition systems from various physical attacks. However, recent research generally focuses on short-distance applications (i.e., phone unlocking) while lacking consideration of long-distance scenes (i.e., surveillance security checks). In order to promote relevant research and fill this gap in the community, we collect a large-scale Surveillance High-Fidelity Mask (SuHiFiMask) dataset captured under 40 surveillance scenes, which has 101 subjects from different age groups with 232 3D attacks (high-fidelity masks), 200 2D attacks (posters, portraits, and screens), and 2 adversarial attacks. In this scene, low image resolution and noise interference are new challenges faced in surveillance FAS. Together with the SuHiFiMask dataset, we propose a Contrastive Quality-Invariance Learning (CQIL) network to alleviate the performance degradation caused by image quality from three aspects: (1) An Image Quality Variable module (IQV) is introduced to recover image information associated with discrimination by combining the super-resolution network. (2) Using generated sample pairs to simulate quality variance distributions to help contrastive learning strategies obtain robust feature representation under quality variation. (3) A Separate Quality Network (SQN) is designed to learn discriminative features independent of image quality. Finally, a large number of experiments verify the quality of the SuHiFiMask dataset and the superiority of the proposed CQIL.  
  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 HUPBA Approved no  
  Call Number (down) Admin @ si @ FLW2024 Serial 3869  
Permanent link to this record
 

 
Author Hao Fang; Ajian Liu; Jun Wan; Sergio Escalera; Hugo Jair Escalante; Zhen Lei edit  url
doi  openurl
  Title Surveillance Face Presentation Attack Detection Challenge Type Conference Article
  Year 2023 Publication Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops Abbreviated Journal  
  Volume Issue Pages 6360-6370  
  Keywords  
  Abstract Face Anti-spoofing (FAS) is essential to secure face recognition systems from various physical attacks. However, most of the studies lacked consideration of long-distance scenarios. Specifically, compared with FAS in traditional scenes such as phone unlocking, face payment, and self-service security inspection, FAS in long-distance such as station squares, parks, and self-service supermarkets are equally important, but it has not been sufficiently explored yet. In order to fill this gap in the FAS community, we collect a large-scale Surveillance High-Fidelity Mask (SuHiFiMask). SuHiFiMask contains 10,195 videos from 101 subjects of different age groups, which are collected by 7 mainstream surveillance cameras. Based on this dataset and protocol-3 for evaluating the robustness of the algorithm under quality changes, we organized a face presentation attack detection challenge in surveillance scenarios. It attracted 180 teams for the development phase with a total of 37 teams qualifying for the final round. The organization team re-verified and re-ran the submitted code and used the results as the final ranking. In this paper, we present an overview of the challenge, including an introduction to the dataset used, the definition of the protocol, the evaluation metrics, and the announcement of the competition results. Finally, we present the top-ranked algorithms and the research ideas provided by the competition for attack detection in long-range surveillance scenarios.  
  Address Vancouver; Canada; June 2023  
  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 CVPRW  
  Notes MSIAU Approved no  
  Call Number (down) Admin @ si @ FLW2023 Serial 3917  
Permanent link to this record
 

 
Author Onur Ferhat; Arcadi Llanza; Fernando Vilariño edit  openurl
  Title Gaze interaction for multi-display systems using natural light eye-tracker Type Conference Article
  Year 2015 Publication 2nd International Workshop on Solutions for Automatic Gaze Data Analysis Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Bielefeld; Germany; September 2015  
  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 SAGA  
  Notes MV;SIAI Approved no  
  Call Number (down) Admin @ si @ FLV2015b Serial 2676  
Permanent link to this record
 

 
Author Onur Ferhat; Arcadi Llanza; Fernando Vilariño edit  doi
isbn  openurl
  Title A Feature-Based Gaze Estimation Algorithm for Natural Light Scenarios Type Conference Article
  Year 2015 Publication Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 Abbreviated Journal  
  Volume 9117 Issue Pages 569-576  
  Keywords Eye tracking; Gaze estimation; Natural light; Webcam  
  Abstract We present an eye tracking system that works with regular webcams. We base our work on open source CVC Eye Tracker [7] and we propose a number of improvements and a novel gaze estimation method. The new method uses features extracted from iris segmentation and it does not fall into the traditional categorization of appearance–based/model–based methods. Our experiments show that our approach reduces the gaze estimation errors by 34 % in the horizontal direction and by 12 % in the vertical direction compared to the baseline system.  
  Address Santiago de Compostela; June 2015  
  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 978-3-319-19389-2 Medium  
  Area Expedition Conference IbPRIA  
  Notes MV;SIAI Approved no  
  Call Number (down) Admin @ si @ FLV2015a Serial 2646  
Permanent link to this record
 

 
Author Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke edit  doi
openurl 
  Title Writer Identification in Old Handwritten Music Scores Type Book Chapter
  Year 2012 Publication Pattern Recognition and Signal Processing in Archaeometry: Mathematical and Computational Solutions for Archaeology Abbreviated Journal  
  Volume Issue Pages 27-63  
  Keywords  
  Abstract The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores. Even though an important amount of compositions contains handwritten text in the music scores, the aim of our work is to use only music notation to determine the author. The steps of the system proposed are the following. First of all, the music sheet is preprocessed and normalized for obtaining a single binarized music line, without the staff lines. Afterwards, 100 features are extracted for every music line, which are subsequently used in a k-NN classifier that compares every feature vector with prototypes stored in a database. By applying feature selection and extraction methods on the original feature set, the performance is increased. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving a recognition rate of about 95%.  
  Address  
  Corporate Author Thesis  
  Publisher IGI-Global Place of Publication Editor Copnstantin Papaodysseus  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number (down) Admin @ si @ FLS2012 Serial 1828  
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Author Alicia Fornes; Josep Llados; Oriol Ramos Terrades; Marçal Rusiñol edit   pdf
openurl 
  Title La Visió per Computador com a Eina per a la Interpretació Automàtica de Fonts Documentals Type Journal
  Year 2016 Publication Lligall, Revista Catalana d'Arxivística Abbreviated Journal  
  Volume 39 Issue Pages 20-46  
  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 DAG; 600.097 Approved no  
  Call Number (down) Admin @ si @ FLR2016 Serial 2897  
Permanent link to this record
 

 
Author Alicia Fornes; Josep Llados; Joana Maria Pujadas-Mora edit  url
isbn  openurl
  Title Browsing of the Social Network of the Past: Information Extraction from Population Manuscript Images Type Book Chapter
  Year 2020 Publication Handwritten Historical Document Analysis, Recognition, and Retrieval – State of the Art and Future Trends Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher World Scientific Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-981-120-323-7 Medium  
  Area Expedition Conference  
  Notes DAG; 600.140; 600.121 Approved no  
  Call Number (down) Admin @ si @ FLP2020 Serial 3350  
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