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Author Pierluigi Casale; Oriol Pujol; Petia Radeva edit  url
doi  isbn
openurl 
  Title Face-to-face social activity detection using data collected with a wearable device Type Conference Article
  Year 2009 Publication (up) 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 5524 Issue Pages 56–63  
  Keywords  
  Abstract 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  
  Address Póvoa de Varzim, Portugal  
  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 978-3-642-02171-8 Medium  
  Area Expedition Conference IbPRIA  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ CPR2009b Serial 1206  
Permanent link to this record
 

 
Author Marco Pedersoli; Jordi Gonzalez; Juan J. Villanueva edit  doi
isbn  openurl
  Title High-Speed Human Detection Using a Multiresolution Cascade of Histograms of Oriented Gradients Type Conference Article
  Year 2009 Publication (up) 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 5524 Issue Pages  
  Keywords  
  Abstract This paper presents a new method for human detection based on a multiresolution cascade of Histograms of Oriented Gradients (HOG) that can highly reduce the computational cost of the detection search without affecting accuracy. The method consists of a cascade of sliding window detectors. Each detector is a Support Vector Machine (SVM) composed by features at different resolution, from coarse for the first level to fine for the last one.
Considering that the spatial stride of the sliding window search is affected by the HOG features size, unlike previous methods based on Adaboost cascades, we can adopt a spatial stride inversely proportional to the features resolution. This produces that the speed-up of the cascade is not only due to the low number of features that need to be computed in the first levels, but also to the lower number of detection windows that needs to be evaluated.
Experimental results shows that our method permits a detection rate comparable with the state of the art, but at the same time a gain in the speed of the detection search of 10-20 times depending on the cascade configuration.
 
  Address Póvoa de Varzim, Portugal  
  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 978-3-642-02171-8 Medium  
  Area Expedition Conference IbPRIA  
  Notes ISE Approved no  
  Call Number ISE @ ise @ PGV2009 Serial 1214  
Permanent link to this record
 

 
Author Bhaskar Chakraborty; Andrew Bagdanov; Jordi Gonzalez edit  doi
isbn  openurl
  Title Towards Real-Time Human Action Recognition Type Conference Article
  Year 2009 Publication (up) 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 5524 Issue Pages  
  Keywords  
  Abstract This work presents a novel approach to human detection based action-recognition in real-time. To realize this goal our method first detects humans in different poses using a correlation-based approach. Recognition of actions is done afterward based on the change of the angular values subtended by various body parts. Real-time human detection and action recognition are very challenging, and most state-of-the-art approaches employ complex feature extraction and classification techniques, which ultimately becomes a handicap for real-time recognition. Our correlation-based method, on the other hand, is computationally efficient and uses very simple gradient-based features. For action recognition angular features of body parts are extracted using a skeleton technique. Results for action recognition are comparable with the present state-of-the-art.  
  Address Póvoa de Varzim, Portugal  
  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 978-3-642-02171-8 Medium  
  Area Expedition Conference IbPRIA  
  Notes ISE Approved no  
  Call Number DAG @ dag @ CBG2009 Serial 1215  
Permanent link to this record
 

 
Author Murad Al Haj; Andrew Bagdanov; Jordi Gonzalez; Xavier Roca edit  doi
isbn  openurl
  Title Robust and Efficient Multipose Face Detection Using Skin Color Segmentation Type Conference Article
  Year 2009 Publication (up) 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 5524 Issue Pages  
  Keywords  
  Abstract In this paper we describe an efficient technique for detecting faces in arbitrary images and video sequences. The approach is based on segmentation of images or video frames into skin-colored blobs using a pixel-based heuristic. Scale and translation invariant features are then computed from these segmented blobs which are used to perform statistical discrimination between face and non-face classes. We train and evaluate our method on a standard, publicly available database of face images and analyze its performance over a range of statistical pattern classifiers. The generalization of our approach is illustrated by testing on an independent sequence of frames containing many faces and non-faces. These experiments indicate that our proposed approach obtains false positive rates comparable to more complex, state-of-the-art techniques, and that it generalizes better to new data. Furthermore, the use of skin blobs and invariant features requires fewer training samples since significantly fewer non-face candidate regions must be considered when compared to AdaBoost-based approaches.  
  Address Springer Berlin Heidelberg  
  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 978-3-642-02171-8 Medium  
  Area Expedition Conference IbPRIA  
  Notes ISE Approved no  
  Call Number DAG @ dag @ ABG2009 Serial 1216  
Permanent link to this record
 

 
Author F. Javier Sanchez; Jorge Bernal edit  url
doi  openurl
  Title Use of Software Tools for Real-time Monitoring of Learning Processes: Application to Compilers subject Type Conference Article
  Year 2018 Publication (up) 4th International Conference of Higher Education Advances Abbreviated Journal  
  Volume Issue Pages 1359-1366  
  Keywords Monitoring; Evaluation tool; Gamification; Student motivation  
  Abstract The effective implementation of the Higher European Education Area has meant a change regarding the focus of the learning process, being now the student at its very center. This shift of focus requires a strong involvement and fluent communication between teachers and students to succeed. Considering the difficulties associated to motivate students to take a more active role in the learning process, we explore how the use of a software tool can help both actors to improve the learning experience. We present a tool that can help students to obtain instantaneous feedback with respect to their progress in the subject as well as providing teachers with useful information about the evolution of knowledge acquisition with respect to each of the subject areas. We compare the performance achieved by students in two academic years: results show an improvement in overall performance which, after observing graphs provided by our tool, can be associated to an increase in students interest in the subject.  
  Address Valencia; June 2018  
  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 HEAD  
  Notes MV; no proj Approved no  
  Call Number Admin @ si @ SaB2018 Serial 3165  
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Author Ana Maria Ares; Jorge Bernal; Maria Jesus Nozal; F. Javier Sanchez; Jose Bernal edit  url
doi  openurl
  Title Results of the use of Kahoot! gamification tool in a course of Chemistry Type Conference Article
  Year 2018 Publication (up) 4th International Conference on Higher Education Advances Abbreviated Journal  
  Volume Issue Pages 1215-1222  
  Keywords  
  Abstract The present study examines the use of Kahoot! as a gamification tool to explore mixed learning strategies. We analyze its use in two different groups of a theoretical subject of the third course of the Degree in Chemistry. An empirical-analytical methodology was used using Kahoot! in two different groups of students, with different frequencies. The academic results of these two group of students were compared between them and with those obtained in the previous course, in which Kahoot! was not employed, with the aim of measuring the evolution in the students´ knowledge. The results showed, in all cases, that the use of Kahoot! has led to a significant increase in the overall marks, and in the number of students who passed the subject. Moreover, some differences were also observed in students´ academic performance according to the group. Finally, it can be concluded that the use of a gamification tool (Kahoot!) in a university classroom had generally improved students´ learning and marks, and that this improvement is more prevalent in those students who have achieved a better Kahoot! performance.  
  Address Valencia; June 2018  
  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 HEAD  
  Notes MV; no proj Approved no  
  Call Number Admin @ si @ ABN2018 Serial 3246  
Permanent link to this record
 

 
Author Jialuo Chen; Mohamed Ali Souibgui; Alicia Fornes; Beata Megyesi edit   pdf
openurl 
  Title Unsupervised Alphabet Matching in Historical Encrypted Manuscript Images Type Conference Article
  Year 2021 Publication (up) 4th International Conference on Historical Cryptology Abbreviated Journal  
  Volume Issue Pages 34-37  
  Keywords  
  Abstract Historical ciphers contain a wide range ofsymbols from various symbol sets. Iden-tifying the cipher alphabet is a prerequi-site before decryption can take place andis a time-consuming process. In this workwe explore the use of image processing foridentifying the underlying alphabet in ci-pher images, and to compare alphabets be-tween ciphers. The experiments show thatciphers with similar alphabets can be suc-cessfully discovered through clustering.  
  Address Virtual; September 2021  
  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 HistoCrypt  
  Notes DAG; 602.230; 600.140; 600.121 Approved no  
  Call Number Admin @ si @ CSF2021 Serial 3617  
Permanent link to this record
 

 
Author Arnau Ramisa; Ramon Lopez de Mantaras; Ricardo Toledo edit  openurl
  Title Comparing Combinations of Feature Regions for Panoramic VSLAM Type Conference Article
  Year 2007 Publication (up) 4th International Conference on Informatics in Control, Automation and Robotics Abbreviated Journal  
  Volume Issue Pages 292–297  
  Keywords  
  Abstract  
  Address Angers (France)  
  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 ICINCO  
  Notes RV;ADAS Approved no  
  Call Number Admin @ si @ RLA2007 Serial 900  
Permanent link to this record
 

 
Author Naveen Onkarappa; Sujay M. Veerabhadrappa; Angel Sappa edit  doi
isbn  openurl
  Title Optical Flow in Onboard Applications: A Study on the Relationship Between Accuracy and Scene Texture Type Conference Article
  Year 2012 Publication (up) 4th International Conference on Signal and Image Processing Abbreviated Journal  
  Volume 221 Issue Pages 257-267  
  Keywords  
  Abstract Optical flow has got a major role in making advanced driver assistance systems (ADAS) a reality. ADAS applications are expected to perform efficiently in all kinds of environments, those are highly probable, that one can drive the vehicle in different kinds of roads, times and seasons. In this work, we study the relationship of optical flow with different roads, that is by analyzing optical flow accuracy on different road textures. Texture measures such as TeX , TeX and TeX are evaluated for this purpose. Further, the relation of regularization weight to the flow accuracy in the presence of different textures is also analyzed. Additionally, we present a framework to generate synthetic sequences of different textures in ADAS scenarios with ground-truth optical flow.  
  Address Coimbatore, India  
  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 1876-1100 ISBN 978-81-322-0996-6 Medium  
  Area Expedition Conference ICSIP  
  Notes ADAS Approved no  
  Call Number Admin @ si @ OVS2012 Serial 2356  
Permanent link to this record
 

 
Author Monica Piñol; Angel Sappa; Ricardo Toledo edit   pdf
doi  isbn
openurl 
  Title MultiTable Reinforcement for Visual Object Recognition Type Conference Article
  Year 2012 Publication (up) 4th International Conference on Signal and Image Processing Abbreviated Journal  
  Volume 221 Issue Pages 469-480  
  Keywords  
  Abstract This paper presents a bag of feature based method for visual object recognition. Our contribution is focussed on the selection of the best feature descriptor. It is implemented by using a novel multi-table reinforcement learning method that selects among five of classical descriptors (i.e., Spin, SIFT, SURF, C-SIFT and PHOW) the one that best describes each image. Experimental results and comparisons are provided showing the improvements achieved with the proposed approach.  
  Address Coimbatore, India  
  Corporate Author Thesis  
  Publisher Springer India Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 1876-1100 ISBN 978-81-322-0996-6 Medium  
  Area Expedition Conference ICSIP  
  Notes ADAS Approved no  
  Call Number Admin @ si @ PST2012 Serial 2157  
Permanent link to this record
 

 
Author Quentin Angermann; Jorge Bernal; Cristina Sanchez Montes; Gloria Fernandez Esparrach; Xavier Gray; Olivier Romain; F. Javier Sanchez; Aymeric Histace edit   pdf
openurl 
  Title Towards Real-Time Polyp Detection in Colonoscopy Videos: Adapting Still Frame-Based Methodologies for Video Sequences Analysis Type Conference Article
  Year 2017 Publication (up) 4th International Workshop on Computer Assisted and Robotic Endoscopy Abbreviated Journal  
  Volume Issue Pages 29-41  
  Keywords Polyp detection; colonoscopy; real time; spatio temporal coherence  
  Abstract Colorectal cancer is the second cause of cancer death in United States: precursor lesions (polyps) detection is key for patient survival. Though colonoscopy is the gold standard screening tool, some polyps are still missed. Several computational systems have been proposed but none of them are used in the clinical room mainly due to computational constraints. Besides, most of them are built over still frame databases, decreasing their performance on video analysis due to the lack of output stability and not coping with associated variability on image quality and polyp appearance. We propose a strategy to adapt these methods to video analysis by adding a spatio-temporal stability module and studying a combination of features to capture polyp appearance variability. We validate our strategy, incorporated on a real-time detection method, on a public video database. Resulting method detects all
polyps under real time constraints, increasing its performance due to our
adaptation strategy.
 
  Address Quebec; Canada; September 2017  
  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 CARE  
  Notes MV; 600.096; 600.075 Approved no  
  Call Number Admin @ si @ ABS2017b Serial 2977  
Permanent link to this record
 

 
Author Alejandro Tabas; Emili Balaguer-Ballester; Laura Igual edit   pdf
doi  isbn
openurl 
  Title Spatial Discriminant ICA for RS-fMRI characterisation Type Conference Article
  Year 2014 Publication (up) 4th International Workshop on Pattern Recognition in Neuroimaging Abbreviated Journal  
  Volume Issue Pages 1-4  
  Keywords  
  Abstract Resting-State fMRI (RS-fMRI) is a brain imaging technique useful for exploring functional connectivity. A major point of interest in RS-fMRI analysis is to isolate connectivity patterns characterising disorders such as for instance ADHD. Such characterisation is usually performed in two steps: first, all connectivity patterns in the data are extracted by means of Independent Component Analysis (ICA); second, standard statistical tests are performed over the extracted patterns to find differences between control and clinical groups. In this work we introduce a novel, single-step, approach for this problem termed Spatial Discriminant ICA. The algorithm can efficiently isolate networks of functional connectivity characterising a clinical group by combining ICA and a new variant of the Fisher’s Linear Discriminant also introduced in this work. As the characterisation is carried out in a single step, it potentially provides for a richer characterisation of inter-class differences. The algorithm is tested using synthetic and real fMRI data, showing promising results in both experiments.  
  Address Tübingen; June 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 978-1-4799-4150-6 Medium  
  Area Expedition Conference PRNI  
  Notes OR;MILAB Approved no  
  Call Number Admin @ si @ TBI2014 Serial 2493  
Permanent link to this record
 

 
Author Pau Torras; Arnau Baro; Alicia Fornes; Lei Kang edit   pdf
openurl 
  Title Improving Handwritten Music Recognition through Language Model Integration Type Conference Article
  Year 2022 Publication (up) 4th International Workshop on Reading Music Systems (WoRMS2022) Abbreviated Journal  
  Volume Issue Pages 42-46  
  Keywords optical music recognition; historical sources; diversity; music theory; digital humanities  
  Abstract Handwritten Music Recognition, especially in the historical domain, is an inherently challenging endeavour; paper degradation artefacts and the ambiguous nature of handwriting make recognising such scores an error-prone process, even for the current state-of-the-art Sequence to Sequence models. In this work we propose a way of reducing the production of statistically implausible output sequences by fusing a Language Model into a recognition Sequence to Sequence model. The idea is leveraging visually-conditioned and context-conditioned output distributions in order to automatically find and correct any mistakes that would otherwise break context significantly. We have found this approach to improve recognition results to 25.15 SER (%) from a previous best of 31.79 SER (%) in the literature.  
  Address November 18, 2022  
  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 WoRMS  
  Notes DAG; 600.121; 600.162; 602.230 Approved no  
  Call Number Admin @ si @ TBF2022 Serial 3735  
Permanent link to this record
 

 
Author Mohamed Ali Souibgui; Y.Kessentini; Alicia Fornes edit   pdf
openurl 
  Title A conditional GAN based approach for distorted camera captured documents recovery Type Conference Article
  Year 2020 Publication (up) 4th Mediterranean Conference on Pattern Recognition and Artificial Intelligence Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Virtual; December 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 MedPRAI  
  Notes DAG; 600.121 Approved no  
  Call Number Admin @ si @ SKF2020 Serial 3450  
Permanent link to this record
 

 
Author Ilke Demir; Dena Bazazian; Adriana Romero; Viktoriia Sharmanska; Lyne P. Tchapmi edit   pdf
doi  openurl
  Title WiCV 2018: The Fourth Women In Computer Vision Workshop Type Conference Article
  Year 2018 Publication (up) 4th Women in Computer Vision Workshop Abbreviated Journal  
  Volume Issue Pages 1941-19412  
  Keywords Conferences; Computer vision; Industries; Object recognition; Engineering profession; Collaboration; Machine learning  
  Abstract We present WiCV 2018 – Women in Computer Vision Workshop to increase the visibility and inclusion of women researchers in computer vision field, organized in conjunction with CVPR 2018. Computer vision and machine learning have made incredible progress over the past years, yet the number of female researchers is still low both in academia and industry. WiCV is organized to raise visibility of female researchers, to increase the collaboration,
and to provide mentorship and give opportunities to femaleidentifying junior researchers in the field. In its fourth year, we are proud to present the changes and improvements over the past years, summary of statistics for presenters and attendees, followed by expectations from future generations.
 
  Address Salt Lake City; USA; June 2018  
  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 WiCV  
  Notes DAG; 600.121; 600.129 Approved no  
  Call Number Admin @ si @ DBR2018 Serial 3222  
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