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Author Joaquin Salas; Wendy Avalos; Rafael Castañeda; Mario Maya edit  openurl
  Title A machine-vision system to measure the parameters describing the performance of a Foucault pendulum Type Journal
  Year 2006 Publication Machine Vision and Applications Abbreviated Journal  
  Volume 17 Issue (up) 2 Pages 133–138  
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  Call Number Admin @ si @ SAC2006 Serial 644  
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Author Oriol Pujol; Sergio Escalera; Petia Radeva edit  openurl
  Title An Incremental Node Embedding Technique for Error Correcting Output Codes Type Journal
  Year 2008 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 41 Issue (up) 2 Pages 713–725  
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  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ PER2008 Serial 942  
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Author Hamdi Dibeklioglu; M.O. Hortas; I. Kosunen; P. Zuzánek; Albert Ali Salah; Theo Gevers edit  doi
openurl 
  Title Design and implementation of an affect-responsive interactive photo frame Type Journal
  Year 2011 Publication Journal on Multimodal User Interfaces Abbreviated Journal JMUI  
  Volume 4 Issue (up) 2 Pages 81-95  
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  Abstract This paper describes an affect-responsive interactive photo-frame application that offers its user a different experience with every use. It relies on visual analysis of activity levels and facial expressions of its users to select responses from a database of short video segments. This ever-growing database is automatically prepared by an offline analysis of user-uploaded videos. The resulting system matches its user’s affect along dimensions of valence and arousal, and gradually adapts its response to each specific user. In an extended mode, two such systems are coupled and feed each other with visual content. The strengths and weaknesses of the system are assessed through a usability study, where a Wizard-of-Oz response logic is contrasted with the fully automatic system that uses affective and activity-based features, either alone, or in tandem.  
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  Publisher Springer–Verlag Place of Publication Editor  
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  ISSN 1783-7677 ISBN Medium  
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  Notes ALTRES;ISE Approved no  
  Call Number Admin @ si @ DHK2011 Serial 1842  
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Author Enric Marti; J.Roncaries; Debora Gil; Aura Hernandez-Sabate; Antoni Gurgui; Ferran Poveda edit  doi
openurl 
  Title PBL On Line: A proposal for the organization, part-time monitoring and assessment of PBL group activities Type Journal
  Year 2015 Publication Journal of Technology and Science Education Abbreviated Journal JOTSE  
  Volume 5 Issue (up) 2 Pages 87-96  
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  Notes IAM; ADAS; 600.076; 600.075 Approved no  
  Call Number Admin @ si @ MRG2015 Serial 2608  
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Author Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; J.Roncaries; Debora Gil edit  doi
openurl 
  Title Automatic evaluation of practices in Moodle for Self Learning in Engineering Type Journal
  Year 2015 Publication Journal of Technology and Science Education Abbreviated Journal JOTSE  
  Volume 5 Issue (up) 2 Pages 97-106  
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  Notes IAM; DAG; 600.075; 600.077 Approved no  
  Call Number Admin @ si @ SRM2015 Serial 2610  
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Author Marc Sunset Perez; Marc Comino Trinidad; Dimosthenis Karatzas; Antonio Chica Calaf; Pere Pau Vazquez Alcocer edit  url
openurl 
  Title Development of general‐purpose projection‐based augmented reality systems Type Journal
  Year 2016 Publication IADIs international journal on computer science and information systems Abbreviated Journal IADIs  
  Volume 11 Issue (up) 2 Pages 1-18  
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  Abstract Despite the large amount of methods and applications of augmented reality, there is little homogenizatio n on the software platforms that support them. An exception may be the low level control software that is provided by some high profile vendors such as Qualcomm and Metaio. However, these provide fine grain modules for e.g. element tracking. We are more co ncerned on the application framework, that includes the control of the devices working together for the development of the AR experience. In this paper we describe the development of a software framework for AR setups. We concentrate on the modular design of the framework, but also on some hard problems such as the calibration stage, crucial for projection – based AR. The developed framework is suitable and has been tested in AR applications using camera – projector pairs, for both fixed and nomadic setups  
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  Notes DAG; 600.084 Approved no  
  Call Number Admin @ si @ SCK2016 Serial 2890  
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Author Patrick Brandao; O. Zisimopoulos; E. Mazomenos; G. Ciutib; Jorge Bernal; M. Visentini-Scarzanell; A. Menciassi; P. Dario; A. Koulaouzidis; A. Arezzo; D.J. Hawkes; D. Stoyanov edit   pdf
url  doi
openurl 
  Title Towards a computed-aided diagnosis system in colonoscopy: Automatic polyp segmentation using convolution neural networks Type Journal
  Year 2018 Publication Journal of Medical Robotics Research Abbreviated Journal JMRR  
  Volume 3 Issue (up) 2 Pages  
  Keywords convolutional neural networks; colonoscopy; computer aided diagnosis  
  Abstract Early diagnosis is essential for the successful treatment of bowel cancers including colorectal cancer (CRC) and capsule endoscopic imaging with robotic actuation can be a valuable diagnostic tool when combined with automated image analysis. We present a deep learning rooted detection and segmentation framework for recognizing lesions in colonoscopy and capsule endoscopy images. We restructure established convolution architectures, such as VGG and ResNets, by converting them into fully-connected convolution networks (FCNs), ne-tune them and study their capabilities for polyp segmentation and detection. We additionally use Shape-from-Shading (SfS) to recover depth and provide a richer representation of the tissue's structure in colonoscopy images. Depth is
incorporated into our network models as an additional input channel to the RGB information and we demonstrate that the resulting network yields improved performance. Our networks are tested on publicly available datasets and the most accurate segmentation model achieved a mean segmentation IU of 47.78% and 56.95% on the ETIS-Larib and CVC-Colon datasets, respectively. For polyp
detection, the top performing models we propose surpass the current state of the art with detection recalls superior to 90% for all datasets tested. To our knowledge, we present the rst work to use FCNs for polyp segmentation in addition to proposing a novel combination of SfS and RGB that boosts performance.
 
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  Notes MV; no menciona Approved no  
  Call Number BZM2018 Serial 2976  
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Author Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate edit  openurl
  Title Análisis 3d de la territorialidad cromosómica en células espermatogénicas: explorando la infertilidad desde un nuevo prisma Type Journal
  Year 2017 Publication Revista Asociación para el Estudio de la Biología de la Reproducción Abbreviated Journal ASEBIR  
  Volume 22 Issue (up) 2 Pages 105  
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  Notes IAM; 600.096; 600.145 Approved no  
  Call Number Admin @ si @ SBG2017d Serial 3042  
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Author Lasse Martensson; Ekta Vats; Anders Hast; Alicia Fornes edit  url
openurl 
  Title In Search of the Scribe: Letter Spotting as a Tool for Identifying Scribes in Large Handwritten Text Corpora Type Journal
  Year 2019 Publication Journal for Information Technology Studies as a Human Science Abbreviated Journal HUMAN IT  
  Volume 14 Issue (up) 2 Pages 95-120  
  Keywords Scribal attribution/ writer identification; digital palaeography; word spotting; mediaeval charters; mediaeval manuscripts  
  Abstract In this article, a form of the so-called word spotting-method is used on a large set of handwritten documents in order to identify those that contain script of similar execution. The point of departure for the investigation is the mediaeval Swedish manuscript Cod. Holm. D 3. The main scribe of this manuscript has yet not been identified in other documents. The current attempt aims at localising other documents that display a large degree of similarity in the characteristics of the script, these being possible candidates for being executed by the same hand. For this purpose, the method of word spotting has been employed, focusing on individual letters, and therefore the process is referred to as letter spotting in the article. In this process, a set of ‘g’:s, ‘h’:s and ‘k’:s have been selected as templates, and then a search has been made for close matches among the mediaeval Swedish charters. The search resulted in a number of charters that displayed great similarities with the manuscript D 3. The used letter spotting method thus proofed to be a very efficient sorting tool localising similar script samples.  
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  Notes DAG; 600.097; 600.140; 600.121 Approved no  
  Call Number Admin @ si @ MVH2019 Serial 3234  
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Author Shifeng Zhang; Ajian Liu; Jun Wan; Yanyan Liang; Guogong Guo; Sergio Escalera; Hugo Jair Escalante; Stan Z. Li edit  url
doi  openurl
  Title CASIA-SURF: A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing Type Journal
  Year 2020 Publication IEEE Transactions on Biometrics, Behavior, and Identity Science Abbreviated Journal TTBIS  
  Volume 2 Issue (up) 2 Pages 182 - 193  
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  Abstract Face anti-spoofing is essential to prevent face recognition systems from a security breach. Much of the progresses have been made by the availability of face anti-spoofing benchmark datasets in recent years. However, existing face anti-spoofing benchmarks have limited number of subjects (≤170) and modalities (≤2), which hinder the further development of the academic community. To facilitate face anti-spoofing research, we introduce a large-scale multi-modal dataset, namely CASIA-SURF, which is the largest publicly available dataset for face anti-spoofing in terms of both subjects and modalities. Specifically, it consists of 1,000 subjects with 21,000 videos and each sample has 3 modalities ( i.e. , RGB, Depth and IR). We also provide comprehensive evaluation metrics, diverse evaluation protocols, training/validation/testing subsets and a measurement tool, developing a new benchmark for face anti-spoofing. Moreover, we present a novel multi-modal multi-scale fusion method as a strong baseline, which performs feature re-weighting to select the more informative channel features while suppressing the less useful ones for each modality across different scales. Extensive experiments have been conducted on the proposed dataset to verify its significance and generalization capability. The dataset is available at https://sites.google.com/qq.com/face-anti-spoofing/welcome/challengecvpr2019?authuser=0  
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  Notes HuPBA; no proj Approved no  
  Call Number Admin @ si @ ZLW2020 Serial 3412  
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Author Gemma Rotger; Francesc Moreno-Noguer; Felipe Lumbreras; Antonio Agudo edit  url
openurl 
  Title Detailed 3D face reconstruction from a single RGB image Type Journal
  Year 2019 Publication Journal of WSCG Abbreviated Journal JWSCG  
  Volume 27 Issue (up) 2 Pages 103-112  
  Keywords 3D Wrinkle Reconstruction; Face Analysis, Optimization.  
  Abstract This paper introduces a method to obtain a detailed 3D reconstruction of facial skin from a single RGB image.
To this end, we propose the exclusive use of an input image without requiring any information about the observed material nor training data to model the wrinkle properties. They are detected and characterized directly from the image via a simple and effective parametric model, determining several features such as location, orientation, width, and height. With these ingredients, we propose to minimize a photometric error to retrieve the final detailed 3D map, which is initialized by current techniques based on deep learning. In contrast with other approaches, we only require estimating a depth parameter, making our approach fast and intuitive. Extensive experimental evaluation is presented in a wide variety of synthetic and real images, including different skin properties and facial
expressions. In all cases, our method outperforms the current approaches regarding 3D reconstruction accuracy, providing striking results for both large and fine wrinkles.
 
  Address 2019/11  
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  Notes MSIAU; 600.086; 600.130; 600.122 Approved no  
  Call Number Admin @ si @ Serial 3708  
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Author J. Pladellorens; M.J. Yzuel; J. Castell; Joan Serrat edit  openurl
  Title Calculo automatico del volumen del ventriculo izquierdo. Comparacion con expertos. Type Journal
  Year 1993 Publication Optica Pura y Aplicada. Abbreviated Journal  
  Volume 26 Issue (up) 3 Pages 685–691  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ PYC1993 Serial 149  
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Author A. Pujol; Juan J. Villanueva edit  openurl
  Title A supervised Modification of the Hausdorff distance for visual shape classification Type Journal
  Year 2002 Publication International Journal of Pattern Recognition and Artificial Intelligence Abbreviated Journal  
  Volume 16 Issue (up) 3 Pages 349-359  
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  Abstract (IF: 0.359)  
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  Notes ISE Approved no  
  Call Number PuV2002 Serial 273  
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Author Josep Llados; Gemma Sanchez edit  openurl
  Title Graph Matching vs. Graph Parsing in Graphics Recognition: A Combined Approach Type Journal
  Year 2004 Publication International Journal of Pattern Recognition and Artificial Intelligence Abbreviated Journal IJPRAI  
  Volume 18 Issue (up) 3 Pages 455–473  
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  Notes DAG; IF: 0.588 Approved no  
  Call Number DAG @ dag @ LlS2004 Serial 445  
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Author Oriol Pujol; Petia Radeva edit  doi
openurl 
  Title Texture Segmentation by Statistical Deformable Models Type Journal
  Year 2004 Publication International Journal of Image and Graphics Abbreviated Journal IJIG  
  Volume 4 Issue (up) 3 Pages 433-452  
  Keywords Texture segmentation, parametric active contours, statistic snakes  
  Abstract Deformable models have received much popularity due to their ability to include high-level knowledge on the application domain into low-level image processing. Still, most proposed active contour models do not sufficiently profit from the application information and they are too generalized, leading to non-optimal final results of segmentation, tracking or 3D reconstruction processes. In this paper we propose a new deformable model defined in a statistical framework to segment objects of natural scenes. We perform a supervised learning of local appearance of the textured objects and construct a feature space using a set of co-occurrence matrix measures. Linear Discriminant Analysis allows us to obtain an optimal reduced feature space where a mixture model is applied to construct a likelihood map. Instead of using a heuristic potential field, our active model is deformed on a regularized version of the likelihood map in order to segment objects characterized by the same texture pattern. Different tests on synthetic images, natural scene and medical images show the advantages of our statistic deformable model.  
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  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ PuR2004a Serial 505  
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