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Author Utkarsh Porwal; Alicia Fornes; Faisal Shafait (eds) edit  doi
isbn  openurl
  Title Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition. 18th International Conference, ICFHR 2022 Type Book Whole
  Year 2022 Publication Frontiers in Handwriting Recognition. Abbreviated Journal  
  Volume 13639 Issue Pages  
  Keywords  
  Abstract  
  Address ICFHR 2022, Hyderabad, India, December 4–7, 2022  
  Corporate Author Thesis  
  Publisher (down) Springer Place of Publication Editor Utkarsh Porwal; Alicia Fornes; Faisal Shafait  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-031-21648-0 Medium  
  Area Expedition Conference ICFHR  
  Notes DAG Approved no  
  Call Number Admin @ si @ PFS2022 Serial 3809  
Permanent link to this record
 

 
Author Jorge Charco; Angel Sappa; Boris X. Vintimilla; Henry Velesaca edit   pdf
doi  isbn
openurl 
  Title Human Body Pose Estimation in Multi-view Environments Type Book Chapter
  Year 2022 Publication ICT Applications for Smart Cities. Intelligent Systems Reference Library Abbreviated Journal  
  Volume 224 Issue Pages 79-99  
  Keywords  
  Abstract This chapter tackles the challenging problem of human pose estimation in multi-view environments to handle scenes with self-occlusions. The proposed approach starts by first estimating the camera pose—extrinsic parameters—in multi-view scenarios; due to few real image datasets, different virtual scenes are generated by using a special simulator, for training and testing the proposed convolutional neural network based approaches. Then, these extrinsic parameters are used to establish the relation between different cameras into the multi-view scheme, which captures the pose of the person from different points of view at the same time. The proposed multi-view scheme allows to robustly estimate human body joints’ position even in situations where they are occluded. This would help to avoid possible false alarms in behavioral analysis systems of smart cities, as well as applications for physical therapy, safe moving assistance for the elderly among other. The chapter concludes by presenting experimental results in real scenes by using state-of-the-art and the proposed multi-view approaches.  
  Address September 2022  
  Corporate Author Thesis  
  Publisher (down) Springer Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title ISRL  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-031-06306-0 Medium  
  Area Expedition Conference  
  Notes MSIAU; MACO Approved no  
  Call Number Admin @ si @ CSV2022b Serial 3810  
Permanent link to this record
 

 
Author Henry Velesaca; Patricia Suarez; Dario Carpio; Rafael E. Rivadeneira; Angel Sanchez; Angel Morera edit   pdf
doi  isbn
openurl 
  Title Video Analytics in Urban Environments: Challenges and Approaches Type Book Chapter
  Year 2022 Publication ICT Applications for Smart Cities Abbreviated Journal  
  Volume 224 Issue Pages 101-121  
  Keywords  
  Abstract This chapter reviews state-of-the-art approaches generally present in the pipeline of video analytics on urban scenarios. A typical pipeline is used to cluster approaches in the literature, including image preprocessing, object detection, object classification, and object tracking modules. Then, a review of recent approaches for each module is given. Additionally, applications and datasets generally used for training and evaluating the performance of these approaches are included. This chapter does not pretend to be an exhaustive review of state-of-the-art video analytics in urban environments but rather an illustration of some of the different recent contributions. The chapter concludes by presenting current trends in video analytics in the urban scenario field.  
  Address September 2022  
  Corporate Author Thesis  
  Publisher (down) Springer Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title ISRL  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-031-06306-0 Medium  
  Area Expedition Conference  
  Notes MSIAU; MACO Approved no  
  Call Number Admin @ si @ VSC2022 Serial 3811  
Permanent link to this record
 

 
Author Angel Sappa (ed) edit  doi
isbn  openurl
  Title ICT Applications for Smart Cities Type Book Whole
  Year 2022 Publication ICT Applications for Smart Cities Abbreviated Journal  
  Volume 224 Issue Pages  
  Keywords Computational Intelligence; Intelligent Systems; Smart Cities; ICT Applications; Machine Learning; Pattern Recognition; Computer Vision; Image Processing  
  Abstract Part of the book series: Intelligent Systems Reference Library (ISRL)

This book is the result of four-year work in the framework of the Ibero-American Research Network TICs4CI funded by the CYTED program. In the following decades, 85% of the world's population is expected to live in cities; hence, urban centers should be prepared to provide smart solutions for problems ranging from video surveillance and intelligent mobility to the solid waste recycling processes, just to mention a few. More specifically, the book describes underlying technologies and practical implementations of several successful case studies of ICTs developed in the following smart city areas:

• Urban environment monitoring
• Intelligent mobility
• Waste recycling processes
• Video surveillance
• Computer-aided diagnose in healthcare systems
• Computer vision-based approaches for efficiency in production processes

The book is intended for researchers and engineers in the field of ICTs for smart cities, as well as to anyone who wants to know about state-of-the-art approaches and challenges on this field.
 
  Address September 2022  
  Corporate Author Thesis  
  Publisher (down) Springer Place of Publication Editor Angel Sappa  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title ISRL  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-031-06306-0 Medium  
  Area Expedition Conference  
  Notes MSIAU; MACO Approved no  
  Call Number Admin @ si @ Sap2022 Serial 3812  
Permanent link to this record
 

 
Author Victoria Ruiz; Angel Sanchez; Jose F. Velez; Bogdan Raducanu edit  doi
isbn  openurl
  Title Waste Classification with Small Datasets and Limited Resources Type Book Chapter
  Year 2022 Publication ICT Applications for Smart Cities. Intelligent Systems Reference Library Abbreviated Journal  
  Volume 224 Issue Pages 185-203  
  Keywords  
  Abstract Automatic waste recycling has become a very important societal challenge nowadays, raising people’s awareness for a cleaner environment and a more sustainable lifestyle. With the transition to Smart Cities, and thanks to advanced ICT solutions, this problem has received a new impulse. The waste recycling focus has shifted from general waste treating facilities to an individual responsibility, where each person should become aware of selective waste separation. The surge of the mobile devices, accompanied by a significant increase in computation power, has potentiated and facilitated this individual role. An automated image-based waste classification mechanism can help with a more efficient recycling and a reduction of contamination from residuals. Despite the good results achieved with the deep learning methodologies for this task, the Achille’s heel is that they require large neural networks which need significant computational resources for training and therefore are not suitable for mobile devices. To circumvent this apparently intractable problem, we will rely on knowledge distillation in order to transfer the network’s knowledge from a larger network (called ‘teacher’) to a smaller, more compact one, (referred as ‘student’) and thus making it possible the task of image classification on a device with limited resources. For evaluation, we considered as ‘teachers’ large architectures such as InceptionResNet or DenseNet and as ‘students’, several configurations of the MobileNets. We used the publicly available TrashNet dataset to demonstrate that the distillation process does not significantly affect system’s performance (e.g. classification accuracy) of the student network.  
  Address September 2022  
  Corporate Author Thesis  
  Publisher (down) Springer Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title ISRL  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-031-06306-0 Medium  
  Area Expedition Conference  
  Notes LAMP Approved no  
  Call Number Admin @ si @ Serial 3813  
Permanent link to this record
 

 
Author Debora Gil; Jaume Garcia; Aura Hernandez-Sabate; Enric Marti edit   pdf
url  doi
openurl 
  Title Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy Type Conference Article
  Year 2010 Publication 8th Medical Imaging Abbreviated Journal  
  Volume 7623 Issue 762304 Pages 304  
  Keywords  
  Abstract Distortion of Left Ventricle (LV) external anatomy is related to some dysfunctions, such as hypertrophy. The architecture of myocardial fibers determines LV electromechanical activation patterns as well as mechanics. Thus, their joined modelling would allow the design of specific interventions (such as peacemaker implantation and LV remodelling) and therapies (such as resynchronization). On one hand, accurate modelling of external anatomy requires either a dense sampling or a continuous infinite dimensional approach, which requires non-Euclidean statistics. On the other hand, computation of fiber models requires statistics on Riemannian spaces. Most approaches compute separate statistical models for external anatomy and fibers architecture. In this work we propose a general mathematical framework based on differential geometry concepts for computing a statistical model including, both, external and fiber anatomy. Our framework provides a continuous approach to external anatomy supporting standard statistics. We also provide a straightforward formula for the computation of the Riemannian fiber statistics. We have applied our methodology to the computation of complete anatomical atlas of canine hearts from diffusion tensor studies. The orientation of fibers over the average external geometry agrees with the segmental description of orientations reported in the literature.  
  Address  
  Corporate Author Thesis  
  Publisher (down) SPIE 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 SPIE  
  Notes IAM Approved no  
  Call Number IAM @ iam @ GGH2010a Serial 1522  
Permanent link to this record
 

 
Author Thierry Brouard; A. Delaplace; Muhammad Muzzamil Luqman; H. Cardot; Jean-Yves Ramel edit  url
doi  isbn
openurl 
  Title Design of Evolutionary Methods Applied to the Learning of Bayesian Nerwork Structures Type Book Chapter
  Year 2010 Publication Bayesian Network Abbreviated Journal  
  Volume Issue Pages 13-37  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher (down) Sciyo Place of Publication Editor Ahmed Rebai  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-953-307-124-4 Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ si @ BDL2010 Serial 1461  
Permanent link to this record
 

 
Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
url  openurl
  Title Current Challenges on Polyp Detection in Colonoscopy Videos: From Region Segmentation to Region Classification. a Pattern Recognition-based Approach.ased Approach Type Conference Article
  Year 2011 Publication 2nd International Workshop on Medical Image Analysis and Descriptionfor Diagnosis Systems Abbreviated Journal  
  Volume Issue Pages 62-71  
  Keywords Medical Imaging, Colonoscopy, Pattern Recognition, Segmentation, Polyp Detection, Region Description, Machine Learning, Real-time.  
  Abstract In this paper we present our approach on real-time polyp detection in colonoscopy videos. Our method consists of three stages: Image Segmentation, Region Description and Image Classification. Taking into account the constraints of our project, we introduce our segmentation system that is based on the model of appearance of the polyp that we have defined after observing real videos from colonoscopy processes. The output of this stage will ideally be a low number of regions of which one of them should cover the whole polyp region (if there is one in the image). This regions will be described in terms of features and, as a result of a machine learning schema, classified based on the values that they have for the several features that we will use on their description. Although we are still on the early stages of the project, we present some preliminary segmentation results that indicates that we are going in a good direction.  
  Address Rome, Italy  
  Corporate Author Thesis  
  Publisher (down) SciTePress Place of Publication Editor Djemal, Khalifa  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area 800 Expedition Conference MIAD  
  Notes MV;SIAI Approved no  
  Call Number IAM @ iam @ BSV2011a Serial 1695  
Permanent link to this record
 

 
Author Joost Van de Weijer; Shida Beigpour edit   pdf
url  isbn
openurl 
  Title The Dichromatic Reflection Model: Future Research Directions and Applications Type Conference Article
  Year 2011 Publication International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications Abbreviated Journal  
  Volume Issue Pages  
  Keywords dblp  
  Abstract The dichromatic reflection model (DRM) predicts that color distributions form a parallelogram in color space, whose shape is defined by the body reflectance and the illuminant color. In this paper we resume the assumptions which led to the DRM and shortly recall two of its main applications domains: color image segmentation and photometric invariant feature computation. After having introduced the model we discuss several limitations of the theory, especially those which are raised once working on real-world uncalibrated images. In addition, we summerize recent extensions of the model which allow to handle more complicated light interactions. Finally, we suggest some future research directions which would further extend its applicability.  
  Address Algarve, Portugal  
  Corporate Author Thesis  
  Publisher (down) SciTePress Place of Publication Editor Mestetskiy, Leonid and Braz, José  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-989-8425-47-8 Medium  
  Area Expedition Conference VISIGRAPP  
  Notes CIC Approved no  
  Call Number Admin @ si @ WeB2011 Serial 1778  
Permanent link to this record
 

 
Author Carles Sanchez; Debora Gil; Antoni Rosell; Albert Andaluz; F. Javier Sanchez edit   pdf
isbn  openurl
  Title Segmentation of Tracheal Rings in Videobronchoscopy combining Geometry and Appearance Type Conference Article
  Year 2013 Publication Proceedings of the International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 1 Issue Pages 153--161  
  Keywords Video-bronchoscopy, tracheal ring segmentation, trachea geometric and appearance model  
  Abstract Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways and minimal invasive interventions. Tracheal procedures are ordinary interventions that require measurement of the percentage of obstructed pathway for injury (stenosis) assessment. Visual assessment of stenosis in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error. Accurate detection of tracheal rings is the basis for automated estimation of the size of stenosed trachea. Processing of videobronchoscopic images acquired at the operating room is a challenging task due to the wide range of artifacts and acquisition conditions. We present a model of the geometric-appearance of tracheal rings for its detection in videobronchoscopic videos. Experiments on sequences acquired at the operating room, show a performance close to inter-observer variability  
  Address Barcelona; February 2013  
  Corporate Author Thesis  
  Publisher (down) SciTePress Place of Publication Portugal Editor Sebastiano Battiato and José Braz  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-989-8565-47-1 Medium  
  Area 800 Expedition Conference VISAPP  
  Notes IAM;MV; 600.044; 600.047; 600.060; 605.203 Approved no  
  Call Number IAM @ iam @ SGR2013 Serial 2123  
Permanent link to this record
 

 
Author Joan M. Nuñez; Debora Gil; Fernando Vilariño edit  doi
openurl 
  Title Finger joint characterization from X-ray images for rheymatoid arthritis assessment Type Conference Article
  Year 2013 Publication 6th International Conference on Biomedical Electronics and Devices Abbreviated Journal  
  Volume Issue Pages 288-292  
  Keywords Rheumatoid Arthritis; X-Ray; Hand Joint; Sclerosis; Sharp Van der Heijde  
  Abstract In this study we propose amodular systemfor automatic rheumatoid arthritis assessment which provides a joint space width measure. A hand joint model is proposed based on the accurate analysis of a X-ray finger joint image sample set. This model shows that the sclerosis and the lower bone are the main necessary features in order to perform a proper finger joint characterization. We propose sclerosis and lower bone detection methods as well as the experimental setup necessary for its performance assessment. Our characterization is used to propose and compute a joint space width score which is shown to be related to the different degrees of arthritis. This assertion is verified by comparing our proposed score with Sharp Van der Heijde score, confirming that the lower our score is the more advanced is the patient affection.  
  Address Barcelona; February 2013  
  Corporate Author Thesis  
  Publisher (down) SciTePress 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 800 Expedition Conference BIODEVICES  
  Notes IAM;MV; 600.057; 600.054;SIAI Approved no  
  Call Number IAM @ iam @ NGV2013 Serial 2196  
Permanent link to this record
 

 
Author Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
doi  openurl
  Title Blood Vessel Characterization in Colonoscopy Images to Improve Polyp Localization Type Conference Article
  Year 2013 Publication Proceedings of the International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 1 Issue Pages 162-171  
  Keywords Colonoscopy; Blood vessel; Linear features; Valley detection  
  Abstract This paper presents an approach to mitigate the contribution of blood vessels to the energy image used at different tasks of automatic colonoscopy image analysis. This goal is achieved by introducing a characterization of endoluminal scene objects which allows us to differentiate between the trace of 2-dimensional visual objects,such as vessels, and shades from 3-dimensional visual objects, such as folds. The proposed characterization is based on the influence that the object shape has in the resulting visual feature, and it leads to the development of a blood vessel attenuation algorithm. A database consisting of manually labelled masks was built in order to test the performance of our method, which shows an encouraging success in blood vessel mitigation while keeping other structures intact. Moreover, by extending our method to the only available polyp localization
algorithm tested on a public database, blood vessel mitigation proved to have a positive influence on the overall performance.
 
  Address Barcelona; February 2013  
  Corporate Author Thesis  
  Publisher (down) SciTePress 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 800 Expedition Conference VISIGRAPP  
  Notes MV; 600.054; 600.057;SIAI Approved no  
  Call Number IAM @ iam @ NBS2013 Serial 2198  
Permanent link to this record
 

 
Author Antoni Gurgui; Debora Gil; Enric Marti edit  url
doi  isbn
openurl 
  Title Laplacian Unitary Domain for Texture Morphing Type Conference Article
  Year 2015 Publication Proceedings of the 10th International Conference on Computer Vision Theory and Applications VISIGRAPP2015 Abbreviated Journal  
  Volume 1 Issue Pages 693-699  
  Keywords Facial; metamorphosis;LaplacianMorphing  
  Abstract Deformation of expressive textures is the gateway to realistic computer synthesis of expressions. By their good mathematical properties and flexible formulation on irregular meshes, most texture mappings rely on solutions to the Laplacian in the cartesian space. In the context of facial expression morphing, this approximation can be seen from the opposite point of view by neglecting the metric. In this paper, we use the properties of the Laplacian in manifolds to present a novel approach to warping expressive facial images in order to generate a morphing between them.  
  Address Munich; Germany; February 2015  
  Corporate Author Thesis  
  Publisher (down) SciTePress Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-989-758-089-5 Medium  
  Area Expedition Conference VISAPP  
  Notes IAM; 600.075 Approved no  
  Call Number Admin @ si @ GGM2015 Serial 2614  
Permanent link to this record
 

 
Author Daniel Rato; Miguel Oliveira; Vitor Santos; Manuel Gomes; Angel Sappa edit  doi
openurl 
  Title A sensor-to-pattern calibration framework for multi-modal industrial collaborative cells Type Journal Article
  Year 2022 Publication Journal of Manufacturing Systems Abbreviated Journal JMANUFSYST  
  Volume 64 Issue Pages 497-507  
  Keywords Calibration; Collaborative cell; Multi-modal; Multi-sensor  
  Abstract Collaborative robotic industrial cells are workspaces where robots collaborate with human operators. In this context, safety is paramount, and for that a complete perception of the space where the collaborative robot is inserted is necessary. To ensure this, collaborative cells are equipped with a large set of sensors of multiple modalities, covering the entire work volume. However, the fusion of information from all these sensors requires an accurate extrinsic calibration. The calibration of such complex systems is challenging, due to the number of sensors and modalities, and also due to the small overlapping fields of view between the sensors, which are positioned to capture different viewpoints of the cell. This paper proposes a sensor to pattern methodology that can calibrate a complex system such as a collaborative cell in a single optimization procedure. Our methodology can tackle RGB and Depth cameras, as well as LiDARs. Results show that our methodology is able to accurately calibrate a collaborative cell containing three RGB cameras, a depth camera and three 3D LiDARs.  
  Address  
  Corporate Author Thesis  
  Publisher (down) Science Direct 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 MSIAU; MACO Approved no  
  Call Number Admin @ si @ ROS2022 Serial 3750  
Permanent link to this record
 

 
Author Eduardo Aguilar; Bhalaji Nagarajan; Beatriz Remeseiro; Petia Radeva edit  doi
openurl 
  Title Bayesian deep learning for semantic segmentation of food images Type Journal Article
  Year 2022 Publication Computers and Electrical Engineering Abbreviated Journal CEE  
  Volume 103 Issue Pages 108380  
  Keywords Deep learning; Uncertainty quantification; Bayesian inference; Image segmentation; Food analysis  
  Abstract Deep learning has provided promising results in various applications; however, algorithms tend to be overconfident in their predictions, even though they may be entirely wrong. Particularly for critical applications, the model should provide answers only when it is very sure of them. This article presents a Bayesian version of two different state-of-the-art semantic segmentation methods to perform multi-class segmentation of foods and estimate the uncertainty about the given predictions. The proposed methods were evaluated on three public pixel-annotated food datasets. As a result, we can conclude that Bayesian methods improve the performance achieved by the baseline architectures and, in addition, provide information to improve decision-making. Furthermore, based on the extracted uncertainty map, we proposed three measures to rank the images according to the degree of noisy annotations they contained. Note that the top 135 images ranked by one of these measures include more than half of the worst-labeled food images.  
  Address October 2022  
  Corporate Author Thesis  
  Publisher (down) Science Direct 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 MILAB Approved no  
  Call Number Admin @ si @ ANR2022 Serial 3763  
Permanent link to this record
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