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Author Salim Jouili; Salvatore Tabbone; Ernest Valveny
Title Evaluation of graph matching measures for documents retrieval Type Conference Article
Year 2009 Publication In proceedings of 8th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages (up) 13–21
Keywords Graph Matching; Graph retrieval; structural representation; Performance Evaluation
Abstract In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used which include line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each grahp distance measure depends on the kind of data and the graph representation technique.
Address La Rochelle, 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 0302-9743 ISBN 978-3-642-13727-3 Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number DAG @ dag @ JTV2009a Serial 1230
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Author Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva
Title Conditional Random Fields for image segmentation in Intravascular Ultrasound Type Conference Article
Year 2010 Publication Medical Image Computing in Catalunya: Graduate Student Workshop Abbreviated Journal
Volume Issue Pages (up) 13–14
Keywords
Abstract We present a Conditional Random Fields based approach for segmenting Intravascular Ultrasond (IVUS) images. The presented method uses a contextual discriminative graphical model to deal with the presence of distorsions and artifacts in IVUS images, that turns the segmentation of interesting regions into a difficult task. An accurate lumen segmentation on IVUS longitudinal images is achieved.
Address Girona
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 MICCAT
Notes MILAB;HUPBA Approved no
Call Number BCNPCL @ bcnpcl @ CPF2010 Serial 1453
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Author Thierry Brouard; A. Delaplace; Muhammad Muzzamil Luqman; H. Cardot; Jean-Yves Ramel
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 (up) 13-37
Keywords
Abstract
Address
Corporate Author Thesis
Publisher 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
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Author Jose Carlos Rubio; Joan Serrat; Antonio Lopez
Title Video Co-segmentation Type Conference Article
Year 2012 Publication 11th Asian Conference on Computer Vision Abbreviated Journal
Volume 7725 Issue Pages (up) 13-24
Keywords
Abstract Segmentation of a single image is in general a highly underconstrained problem. A frequent approach to solve it is to somehow provide prior knowledge or constraints on how the objects of interest look like (in terms of their shape, size, color, location or structure). Image co-segmentation trades the need for such knowledge for something much easier to obtain, namely, additional images showing the object from other viewpoints. Now the segmentation problem is posed as one of differentiating the similar object regions in all the images from the more varying background. In this paper, for the first time, we extend this approach to video segmentation: given two or more video sequences showing the same object (or objects belonging to the same class) moving in a similar manner, we aim to outline its region in all the frames. In addition, the method works in an unsupervised manner, by learning to segment at testing time. We compare favorably with two state-of-the-art methods on video segmentation and report results on benchmark videos.
Address Daejeon, Korea
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 978-3-642-37443-2 Medium
Area Expedition Conference ACCV
Notes ADAS Approved no
Call Number Admin @ si @ RSL2012d Serial 2153
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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 1957 Issue Pages (up) 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 Julio C. S. Jacques Junior; Agata Lapedriza; Cristina Palmero; Xavier Baro; Sergio Escalera
Title Person Perception Biases Exposed: Revisiting the First Impressions Dataset Type Conference Article
Year 2021 Publication IEEE Winter Conference on Applications of Computer Vision Abbreviated Journal
Volume Issue Pages (up) 13-21
Keywords
Abstract This work revisits the ChaLearn First Impressions database, annotated for personality perception using pairwise comparisons via crowdsourcing. We analyse for the first time the original pairwise annotations, and reveal existing person perception biases associated to perceived attributes like gender, ethnicity, age and face attractiveness.
We show how person perception bias can influence data labelling of a subjective task, which has received little attention from the computer vision and machine learning communities by now. We further show that the mechanism used to convert pairwise annotations to continuous values may magnify the biases if no special treatment is considered. The findings of this study are relevant for the computer vision community that is still creating new datasets on subjective tasks, and using them for practical applications, ignoring these perceptual biases.
Address Virtual; January 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 WACV
Notes HUPBA Approved no
Call Number Admin @ si @ JLP2021 Serial 3533
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Author Graham D. Finlayson; Javier Vazquez; Fufu Fang
Title The Discrete Cosine Maximum Ignorance Assumption Type Conference Article
Year 2021 Publication 29th Color and Imaging Conference Abbreviated Journal
Volume Issue Pages (up) 13-18
Keywords
Abstract the performance of colour correction algorithms are dependent on the reflectance sets used. Sometimes, when the testing reflectance set is changed the ranking of colour correction algorithms also changes. To remove dependence on dataset we can
make assumptions about the set of all possible reflectances. In the Maximum Ignorance with Positivity (MIP) assumption we assume that all reflectances with per wavelength values between 0 and 1 are equally likely. A weakness in the MIP is that it fails to take into account the correlation of reflectance functions between
wavelengths (many of the assumed reflectances are, in reality, not possible).
In this paper, we take the view that the maximum ignorance assumption has merit but, hitherto it has been calculated with respect to the wrong coordinate basis. Here, we propose the Discrete Cosine Maximum Ignorance assumption (DCMI), where
all reflectances that have coordinates between max and min bounds in the Discrete Cosine Basis coordinate system are equally likely.
Here, the correlation between wavelengths is encoded and this results in the set of all plausible reflectances ’looking like’ typical reflectances that occur in nature. This said the DCMI model is also a superset of all measured reflectance sets.
Experiments show that, in colour correction, adopting the DCMI results in similar colour correction performance as using a particular reflectance set.
Address Virtual; November 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 CIC
Notes CIC Approved no
Call Number FVF2021 Serial 3596
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Author Meysam Madadi; Sergio Escalera; Jordi Gonzalez; Xavier Roca; Felipe Lumbreras
Title Multi-part body segmentation based on depth maps for soft biometry analysis Type Journal Article
Year 2015 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 56 Issue Pages (up) 14-21
Keywords 3D shape context; 3D point cloud alignment; Depth maps; Human body segmentation; Soft biometry analysis
Abstract This paper presents a novel method extracting biometric measures using depth sensors. Given a multi-part labeled training data, a new subject is aligned to the best model of the dataset, and soft biometrics such as lengths or circumference sizes of limbs and body are computed. The process is performed by training relevant pose clusters, defining a representative model, and fitting a 3D shape context descriptor within an iterative matching procedure. We show robust measures by applying orthogonal plates to body hull. We test our approach in a novel full-body RGB-Depth data set, showing accurate estimation of soft biometrics and better segmentation accuracy in comparison with random forest approach without requiring large training data.
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; ISE; ADAS; 600.076;600.049; 600.063; 600.054; 302.018;MILAB Approved no
Call Number Admin @ si @ MEG2015 Serial 2588
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Author Miquel Ferrer; Ernest Valveny; F. Serratosa; Horst Bunke
Title Exact Median Graph Computation via Graph Embedding Type Conference Article
Year 2008 Publication 12th International Workshop on Structural and Syntactic Pattern Recognition Abbreviated Journal
Volume 5324 Issue Pages (up) 15–24
Keywords
Abstract
Address Orlando – Florida (USA)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference SSPR
Notes DAG Approved no
Call Number DAG @ dag @ FVS2008b Serial 1076
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Author Lluis Pere de las Heras; Oriol Ramos Terrades; Sergi Robles; Gemma Sanchez
Title CVC-FP and SGT: a new database for structural floor plan analysis and its groundtruthing tool Type Journal Article
Year 2015 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 18 Issue 1 Pages (up) 15-30
Keywords
Abstract Recent results on structured learning methods have shown the impact of structural information in a wide range of pattern recognition tasks. In the field of document image analysis, there is a long experience on structural methods for the analysis and information extraction of multiple types of documents. Yet, the lack of conveniently annotated and free access databases has not benefited the progress in some areas such as technical drawing understanding. In this paper, we present a floor plan database, named CVC-FP, that is annotated for the architectural objects and their structural relations. To construct this database, we have implemented a groundtruthing tool, the SGT tool, that allows to make specific this sort of information in a natural manner. This tool has been made for general purpose groundtruthing: It allows to define own object classes and properties, multiple labeling options are possible, grants the cooperative work, and provides user and version control. We finally have collected some of the recent work on floor plan interpretation and present a quantitative benchmark for this database. Both CVC-FP database and the SGT tool are freely released to the research community to ease comparisons between methods and boost reproducible research.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1433-2833 ISBN Medium
Area Expedition Conference
Notes DAG; ADAS; 600.061; 600.076; 600.077 Approved no
Call Number Admin @ si @ HRR2015 Serial 2567
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Author Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich
Title Perception Based Representations for Computational Colour Type Conference Article
Year 2011 Publication 3rd International Workshop on Computational Color Imaging Abbreviated Journal
Volume 6626 Issue Pages (up) 16-30
Keywords colour perception, induction, naming, psychophysical data, saliency, segmentation
Abstract The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space.
Address Milan, Italy
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Editor Raimondo Schettini, Shoji Tominaga, Alain Trémeau
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-20403-6 Medium
Area Expedition Conference CCIW
Notes CIC Approved no
Call Number Admin @ si @ VMB2011 Serial 1733
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Author Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Michael Felsberg; J.Laaksonen
Title Compact color texture description for texture classification Type Journal Article
Year 2015 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 51 Issue Pages (up) 16-22
Keywords
Abstract Describing textures is a challenging problem in computer vision and pattern recognition. The classification problem involves assigning a category label to the texture class it belongs to. Several factors such as variations in scale, illumination and viewpoint make the problem of texture description extremely challenging. A variety of histogram based texture representations exists in literature.
However, combining multiple texture descriptors and assessing their complementarity is still an open research problem. In this paper, we first show that combining multiple local texture descriptors significantly improves the recognition performance compared to using a single best method alone. This
gain in performance is achieved at the cost of high-dimensional final image representation. To counter this problem, we propose to use an information-theoretic compression technique to obtain a compact texture description without any significant loss in accuracy. In addition, we perform a comprehensive
evaluation of pure color descriptors, popular in object recognition, for the problem of texture classification. Experiments are performed on four challenging texture datasets namely, KTH-TIPS-2a, KTH-TIPS-2b, FMD and Texture-10. The experiments clearly demonstrate that our proposed compact multi-texture approach outperforms the single best texture method alone. In all cases, discriminative color names outperforms other color features for texture classification. Finally, we show that combining discriminative color names with compact texture representation outperforms state-of-the-art methods by 7:8%, 4:3% and 5:0% on KTH-TIPS-2a, KTH-TIPS-2b and Texture-10 datasets respectively.
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 LAMP; 600.068; 600.079;ADAS Approved no
Call Number Admin @ si @ KRW2015a Serial 2587
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Author Lluis Pere de las Heras; Gemma Sanchez
Title And-Or Graph Grammar for Architectural Floorplan Representation, Learning and Recognition. A Semantic, Structural and Hierarchical Model Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages (up) 17-24
Keywords
Abstract This paper presents a syntactic model for architectural floor plan interpretation. A stochastic image grammar over an And-Or graph is inferred to represent the hierarchical, structural and semantic relations between elements of all possible floor plans. This grammar is augmented with three different probabilistic models, learnt from a training set, to account the frequency of that relations. Then, a Bottom-Up/Top-Down parser with a pruning strategy has been used for floor plan recognition. For a given input, the parser generates the most probable parse graph for that document. This graph not only contains the structural and semantic relations of its elements, but also its hierarchical composition, that allows to interpret the floor plan at different levels of abstraction.
Address Las Palmas de Gran Canaria. Spain
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 978-3-642-21256-7 Medium
Area Expedition Conference IbPRIA
Notes DAG Approved no
Call Number Admin @ si @ HeS2011 Serial 1736
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Author Kaida Xiao; Chenyang Fu; Dimosthenis Karatzas; Sophie Wuerger
Title Visual Gamma Correction for LCD Displays Type Journal Article
Year 2011 Publication Displays Abbreviated Journal DIS
Volume 32 Issue 1 Pages (up) 17-23
Keywords Display calibration; Psychophysics ; Perceptual; Visual gamma correction; Luminance matching; Observer-based calibration
Abstract An improved method for visual gamma correction is developed for LCD displays to increase the accuracy of digital colour reproduction. Rather than utilising a photometric measurement device, we use observ- ers’ visual luminance judgements for gamma correction. Eight half tone patterns were designed to gen- erate relative luminances from 1/9 to 8/9 for each colour channel. A psychophysical experiment was conducted on an LCD display to find the digital signals corresponding to each relative luminance by visually matching the half-tone background to a uniform colour patch. Both inter- and intra-observer vari- ability for the eight luminance matches in each channel were assessed and the luminance matches proved to be consistent across observers (DE00 < 3.5) and repeatable (DE00 < 2.2). Based on the individual observer judgements, the display opto-electronic transfer function (OETF) was estimated by using either a 3rd order polynomial regression or linear interpolation for each colour channel. The performance of the proposed method is evaluated by predicting the CIE tristimulus values of a set of coloured patches (using the observer-based OETFs) and comparing them to the expected CIE tristimulus values (using the OETF obtained from spectro-radiometric luminance measurements). The resulting colour differences range from 2 to 4.6 DE00. We conclude that this observer-based method of visual gamma correction is useful to estimate the OETF for LCD displays. Its major advantage is that no particular functional relationship between digital inputs and luminance outputs has to be assumed.
Address
Corporate Author Thesis
Publisher Elsevier 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 Approved no
Call Number Admin @ si @ XFK2011 Serial 1815
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Author Ernest Valveny; Oriol Ramos Terrades; Joan Mas; Marçal Rusiñol
Title Interactive Document Retrieval and Classification. Type Book Chapter
Year 2013 Publication Multimodal Interaction in Image and Video Applications Abbreviated Journal
Volume 48 Issue Pages (up) 17-30
Keywords
Abstract In this chapter we describe a system for document retrieval and classification following the interactive-predictive framework. In particular, the system addresses two different scenarios of document analysis: document classification based on visual appearance and logo detection. These two classical problems of document analysis are formulated following the interactive-predictive model, taking the user interaction into account to make easier the process of annotating and labelling the documents. A system implementing this model in a real scenario is presented and analyzed. This system also takes advantage of active learning techniques to speed up the task of labelling the documents.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor Angel Sappa; Jordi Vitria
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ VRM2013 Serial 2341
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