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Author Ole Vilhelm-Larsen; Petia Radeva; Enric Marti
Title Guidelines for choosing optimal parameters of elasticity for snakes Type Book Chapter
Year 1995 Publication Computer Analysis Of Images And Patterns Abbreviated Journal LNCS
Volume (up) 970 Issue Pages 106-113
Keywords
Abstract This paper proposes a guidance in the process of choosing and using the parameters of elasticity of a snake in order to obtain a precise segmentation. A new two step procedure is defined based on upper and lower bounds on the parameters. Formulas, by which these bounds can be calculated for real images where parts of the contour may be missing, are presented. Experiments on segmentation of bone structures in X-ray images have verified the usefulness of the new procedure.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MILAB;IAM Approved no
Call Number IAM @ iam @ LRM1995b Serial 1558
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Author Josep Llados; Gemma Sanchez; Enric Marti
Title A string based method to recognize symbols and structural textures in architectural plans Type Book Chapter
Year 1998 Publication Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers Abbreviated Journal LNCS
Volume (up) 1389 Issue 1998 Pages 91-103
Keywords
Abstract This paper deals with the recognition of symbols and structural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clustering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the similarity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion.
Address
Corporate Author Thesis
Publisher Springer Link Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title LNCS Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes DAG; IAM Approved no
Call Number IAM @ iam @ SLE1998 Serial 1573
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Author Rafael E. Rivadeneira; Angel Sappa; Boris X. Vintimilla
Title Thermal Image Super-Resolution: A Novel Unsupervised Approach Type Conference Article
Year 2022 Publication International Joint Conference on Computer Vision, Imaging and Computer Graphics Abbreviated Journal
Volume (up) 1474 Issue Pages 495–506
Keywords
Abstract This paper proposes the use of a CycleGAN architecture for thermal image super-resolution under a transfer domain strategy, where middle-resolution images from one camera are transferred to a higher resolution domain of another camera. The proposed approach is trained with a large dataset acquired using three thermal cameras at different resolutions. An unsupervised learning process is followed to train the architecture. Additional loss function is proposed trying to improve results from the state of the art approaches. Following the first thermal image super-resolution challenge (PBVS-CVPR2020) evaluations are performed. A comparison with previous works is presented showing the proposed approach reaches the best results.
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 VISIGRAPP
Notes MSIAU; 600.130 Approved no
Call Number Admin @ si @ RSV2022d Serial 3776
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Author Pedro Herruzo; Marc Bolaños; Petia Radeva
Title Can a CNN Recognize Catalan Diet? Type Book Chapter
Year 2016 Publication AIP Conference Proceedings Abbreviated Journal
Volume (up) 1773 Issue Pages
Keywords
Abstract CoRR abs/1607.08811
Nowadays, we can find several diseases related to the unhealthy diet habits of the population, such as diabetes, obesity, anemia, bulimia and anorexia. In many cases, these diseases are related to the food consumption of people. Mediterranean diet is scientifically known as a healthy diet that helps to prevent many metabolic diseases. In particular, our work focuses on the recognition of Mediterranean food and dishes. The development of this methodology would allow to analise the daily habits of users with wearable cameras, within the topic of lifelogging. By using automatic mechanisms we could build an objective tool for the analysis of the patient’s behavior, allowing specialists to discover unhealthy food patterns and understand the user’s lifestyle.
With the aim to automatically recognize a complete diet, we introduce a challenging multi-labeled dataset related to Mediter-ranean diet called FoodCAT. The first type of label provided consists of 115 food classes with an average of 400 images per dish, and the second one consists of 12 food categories with an average of 3800 pictures per class. This dataset will serve as a basis for the development of automatic diet recognition. In this context, deep learning and more specifically, Convolutional Neural Networks (CNNs), currently are state-of-the-art methods for automatic food recognition. In our work, we compare several architectures for image classification, with the purpose of diet recognition. Applying the best model for recognising food categories, we achieve a top-1 accuracy of 72.29%, and top-5 of 97.07%. In a complete diet recognition of dishes from Mediterranean diet, enlarged with the Food-101 dataset for international dishes recognition, we achieve a top-1 accuracy of 68.07%, and top-5 of 89.53%, for a total of 115+101 food classes.
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 MILAB Approved no
Call Number Admin @ si @ HBR2016 Serial 2837
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Author Ernest Valveny; Enric Marti
Title Deformable Template Matching within a Bayesian Framework for Hand-Written Graphic Symbol Recognition Type Journal Article
Year 2000 Publication Graphics Recognition Recent Advances Abbreviated Journal
Volume (up) 1941 Issue Pages 193-208
Keywords
Abstract We describe a method for hand-drawn symbol recognition based on deformable template matching able to handle uncertainty and imprecision inherent to hand-drawing. Symbols are represented as a set of straight lines and their deformations as geometric transformations of these lines. Matching, however, is done over the original binary image to avoid loss of information during line detection. It is defined as an energy minimization problem, using a Bayesian framework which allows to combine fidelity to ideal shape of the symbol and flexibility to modify the symbol in order to get the best fit to the binary input image. Prior to matching, we find the best global transformation of the symbol to start the recognition process, based on the distance between symbol lines and image lines. We have applied this method to the recognition of dimensions and symbols in architectural floor plans and we show its flexibility to recognize distorted symbols.
Address
Corporate Author Springer Verlag Thesis
Publisher Springer Verlag 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;IAM; Approved no
Call Number IAM @ iam @ MVA2000 Serial 1655
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Author Sergio Alloza; Flavio Escribano; Sergi Delgado; Ciprian Corneanu; Sergio Escalera
Title XBadges. Identifying and training soft skills with commercial video games Improving persistence, risk taking & spatial reasoning with commercial video games and facial and emotional recognition system Type Conference Article
Year 2017 Publication 4th Congreso de la Sociedad Española para las Ciencias del Videojuego Abbreviated Journal
Volume (up) 1957 Issue Pages 13-28
Keywords Video Games; Soft Skills; Training; Skilling Development; Emotions; Cognitive Abilities; Flappy Bird; Pacman; Tetris
Abstract XBadges is a research project based on the hypothesis that commercial video games (nonserious games) can train soft skills. We measure persistence, patial reasoning and risk taking before and after subjects paticipate in controlled game playing sessions.
In addition, we have developed an automatic facial expression recognition system capable of inferring their emotions while playing, allowing us to study the role of emotions in soft skills acquisition. We have used Flappy Bird, Pacman and Tetris for assessing changes in persistence, risk taking and spatial reasoning respectively.
Results show how playing Tetris significantly improves spatial reasoning and how playing Pacman significantly improves prudence in certain areas of behavior. As for emotions, they reveal that being concentrated helps to improve performance and skills acquisition. Frustration is also shown as a key element. With the results obtained we are able to glimpse multiple applications in areas which need soft skills development.
Address Barcelona; June 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 COSECIVI; CEUR-WS
Notes HUPBA; no menciona Approved no
Call Number Admin @ si @ AED2017 Serial 3065
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Author Mirko Arnold; Anarta Ghosh; Stephen Ameling; G Lacey
Title Automatic segmentation and inpainting of specular highlights for endoscopic imaging Type Journal Article
Year 2010 Publication EURASIP Journal on Image and Video Processing Abbreviated Journal EURASIP JIVP
Volume (up) 2010 Issue 9 Pages
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 800 Expedition Conference
Notes MV Approved no
Call Number fernando @ fernando @ Serial 2423
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Author Laura Lopez-Fuentes; Alessandro Farasin; Harald Skinnemoen; Paolo Garza
Title Deep Learning models for passability detection of flooded roads Type Conference Article
Year 2018 Publication MediaEval 2018 Multimedia Benchmark Workshop Abbreviated Journal
Volume (up) 2283 Issue Pages
Keywords
Abstract In this paper we study and compare several approaches to detect floods and evidence for passability of roads by conventional means in Twitter. We focus on tweets containing both visual information (a picture shared by the user) and metadata, a combination of text and related extra information intrinsic to the Twitter API. This work has been done in the context of the MediaEval 2018 Multimedia Satellite Task.
Address Sophia Antipolis; France; October 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 MediaEval
Notes LAMP; 600.084; 600.109; 600.120 Approved no
Call Number Admin @ si @ LFS2018 Serial 3224
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Author Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti
Title Symbol recognition: current advances and perspectives Type Book Chapter
Year 2002 Publication Graphics Recognition Algorithms And Applications Abbreviated Journal LNCS
Volume (up) 2390 Issue Pages 104-128
Keywords
Abstract The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.
Address London, UK
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Editor Dorothea Blostein and Young- Bin Kwon
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 3-540-44066-6 Medium
Area Expedition Conference GREC
Notes DAG; IAM; Approved no
Call Number IAM @ iam @ LVS2002 Serial 1572
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Author Francesc Tous; Agnes Borras; Robert Benavente; Ramon Baldrich; Maria Vanrell; Josep Llados
Title Textual Descriptions for Browsing People by Visual Apperance. Type Book Chapter
Year 2002 Publication Lecture Notes in Artificial Intelligence Abbreviated Journal
Volume (up) 2504 Issue Pages 419-429
Keywords
Abstract This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building
Address
Corporate Author Thesis
Publisher Springer Verlag 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;CIC Approved no
Call Number CAT @ cat @ TBB2002b Serial 319
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Author Agnes Borras; Francesc Tous; Josep Llados; Maria Vanrell
Title High-Level Clothes Description Based on Color-Texture and Structural Features Type Book Chapter
Year 2003 Publication Lecture Notes in Computer Science Abbreviated Journal
Volume (up) 2652 Issue Pages 108–116
Keywords
Abstract This work is a part of a surveillance system where content- based image retrieval is done in terms of people appearance. Given an image of a person, our work provides an automatic description of his clothing according to the colour, texture and structural composition of its garments. We present a two-stage process composed by image segmentation and a region-based interpretation. We segment an image by modelling it due to an attributed graph and applying a hybrid method that follows a split-and-merge strategy. We propose the interpretation of five cloth combinations that are modelled in a graph structure in terms of region features. The interpretation is viewed as a graph matching with an associated cost between the segmentation and the cloth models. Fi- nally, we have tested the process with a ground-truth of one hundred images.
Address Springer-Verlag
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;CIC Approved no
Call Number CAT @ cat @ BTL2003a Serial 368
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Author Debora Gil; Petia Radeva
Title Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling Type Book Chapter
Year 2003 Publication Energy Minimization Methods In Computer Vision And Pattern Recognition Abbreviated Journal LNCS
Volume (up) 2683 Issue Pages 357-372
Keywords Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature
Abstract Poor convergence to concave shapes is a main limitation of snakes as a standard segmentation and shape modelling technique. The gradient of the external energy of the snake represents a force that pushes the snake into concave regions, as its internal energy increases when new inexion points are created. In spite of the improvement of the external energy by the gradient vector ow technique, highly non convex shapes can not be obtained, yet. In the present paper, we develop a new external energy based on the geometry of the curve to be modelled. By tracking back the deformation of a curve that evolves by minimum curvature ow, we construct a distance map that encapsulates the natural way of adapting to non convex shapes. The gradient of this map, which we call curvature vector ow (CVF), is capable of attracting a snake towards any contour, whatever its geometry. Our experiments show that, any initial snake condition converges to the curve to be modelled in optimal time.
Address
Corporate Author Thesis
Publisher Springer, Berlin Place of Publication Lisbon, PORTUGAL Editor Springer, B.
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 3-540-40498-8 Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GIR2003b Serial 1535
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Author Ernest Valveny; Philippe Dosch
Title Performance Evaluation of Symbol Recognition Type Book Chapter
Year 2004 Publication Document Analysis Systems Abbreviated Journal LNCS
Volume (up) 3163 Issue Pages 354–365
Keywords
Abstract
Address Springer-Verlag
Corporate Author Thesis
Publisher Place of Publication Editor S. Marinai, A. Dengel (Eds.),
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 3-540-23060-2 Medium
Area Expedition Conference
Notes DAG Approved no
Call Number DAG @ dag @ VaD2004a Serial 502
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Author Joel Barajas; Jaume Garcia; Karla Lizbeth Caballero; Francesc Carreras; Sandra Pujades; Petia Radeva
Title Correction of Misalignment Artifacts Among 2-D Cardiac MR Images in 3-D Space Type Conference Article
Year 2006 Publication 1st International Wokshop on Computer Vision for Intravascular and Intracardiac Imaging (CVII’06) Abbreviated Journal
Volume (up) 3217 Issue Pages 114-121
Keywords
Abstract Cardiac Magnetic Resonance images offer the opportunity to study the heart in detail. One of the main issues in its modelling is to create an accurate 3-D reconstruction of the left ventricle from 2-D views. A first step to achieve this goal is the correct registration among the different image planes due to patient movements. In this article, we present an accurate method to correct displacement artifacts using the Normalized Mutual Information. Here, the image views are treated as planes in order to diminish the approximation error caused by the association of a certain thickness, and moved simultaneously to avoid any kind of bias in the alignment process. This method has been validated using real and syntectic plane displacements, yielding promising results.
Address
Corporate Author Thesis
Publisher Place of Publication Copenhagen (Denmark) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-3-540-22977-3 Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ BGC2006 Serial 1485
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Author Misael Rosales; Petia Radeva; Oriol Rodriguez; Debora Gil
Title Suppression of IVUS Image Rotation. A Kinematic Approach Type Book Chapter
Year 2005 Publication Functional Imaging and Modeling of the Heart Abbreviated Journal LNCS
Volume (up) 3504 Issue Pages 889-892
Keywords
Abstract IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology.
Address
Corporate Author Thesis
Publisher Springer Berlin / Heidelberg Place of Publication Editor Frangi, Alejandro and Radeva, Petia and Santos, Andres and Hernandez, Monica
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS
Series Volume 3504 Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ RRR2005 Serial 1645
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