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Author Fernando Vilariño; Enric Marti
Title New didactic techniques in the EHES applying mobile technologies Type Miscellaneous
Year 2008 Publication (up) Agencia de Gestio d´Ajuts Universitaris I de Recerca (AGAUR), Generalitat de Catalunya Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Agencia de Gestió d’Ajuts Universitaris I de Recerca (AGAUR), Generalitat de Catalunya 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 Agencia de Gestio d´Ajuts Universitaris I de Recerca (AGAUR), Generalitat de Catalunya Expedition Conference
Notes MILAB;IAM;MV;SIAI Approved no
Call Number IAM @ iam @ VIM2008 Serial 1664
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Author Alvaro Cepero; Albert Clapes; Sergio Escalera
Title Automatic non-verbal communication skills analysis: a quantitative evaluation Type Journal Article
Year 2015 Publication (up) AI Communications Abbreviated Journal AIC
Volume 28 Issue 1 Pages 87-101
Keywords Social signal processing; human behavior analysis; multi-modal data description; multi-modal data fusion; non-verbal communication analysis; e-Learning
Abstract The oral communication competence is defined on the top of the most relevant skills for one's professional and personal life. Because of the importance of communication in our activities of daily living, it is crucial to study methods to evaluate and provide the necessary feedback that can be used in order to improve these communication capabilities and, therefore, learn how to express ourselves better. In this work, we propose a system capable of evaluating quantitatively the quality of oral presentations in an automatic fashion. The system is based on a multi-modal RGB, depth, and audio data description and a fusion approach in order to recognize behavioral cues and train classifiers able to eventually predict communication quality levels. The performance of the proposed system is tested on a novel dataset containing Bachelor thesis' real defenses, presentations from an 8th semester Bachelor courses, and Master courses' presentations at Universitat de Barcelona. Using as groundtruth the marks assigned by actual instructors, our system achieves high performance categorizing and ranking presentations by their quality, and also making real-valued mark predictions.
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 0921-7126 ISBN Medium
Area Expedition Conference
Notes HUPBA;MILAB Approved no
Call Number Admin @ si @ CCE2015 Serial 2549
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Author Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez
Title Semantic Annotation of Complex Human Scenes for Multimedia Surveillance Type Conference Article
Year 2007 Publication (up) AI* Artificial Intelligence and Human–Oriented Computing. 10th Congress of the Italian Association for Artificial Intelligence, Abbreviated Journal
Volume 4733 Issue Pages 698–709
Keywords
Abstract
Address Roma (Italy)
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 AI
Notes ISE Approved no
Call Number ISE @ ise @ FBR2007a Serial 920
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Author Pedro Herruzo; Marc Bolaños; Petia Radeva
Title Can a CNN Recognize Catalan Diet? Type Book Chapter
Year 2016 Publication (up) AIP Conference Proceedings Abbreviated Journal
Volume 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 Bogdan Raducanu; Fadi Dornaika
Title Dynamic Vs. Static Recognition of Facial Expressions Type Book Chapter
Year 2008 Publication (up) Ambient Intelligence. European Conference Abbreviated Journal
Volume 5355 Issue Pages 13–25
Keywords
Abstract
Address Nuremberg (Germany)
Corporate Author Thesis
Publisher Place of Publication Editor Rabuñal
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference AMI
Notes OR; MV Approved no
Call Number BCNPCL @ bcnpcl @ RaD2008 Serial 1035
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Author Maurizio Mencuccini; Jordi Martinez-Vilalta; Josep Piñol; Lasse Loepfe; Mireia Burnat ; Xavier Alvarez; Juan Camacho; Debora Gil
Title A quantitative and statistically robust method for the determination of xylem conduit spatial distribution Type Journal Article
Year 2010 Publication (up) American Journal of Botany Abbreviated Journal AJB
Volume 97 Issue 8 Pages 1247-1259
Keywords Geyer; hydraulic conductivity; point pattern analysis; Ripley; Spatstat; vessel clusters; xylem anatomy; xylem network
Abstract Premise of the study: Because of their limited length, xylem conduits need to connect to each other to maintain water transport from roots to leaves. Conduit spatial distribution in a cross section plays an important role in aiding this connectivity. While indices of conduit spatial distribution already exist, they are not well defined statistically. * Methods: We used point pattern analysis to derive new spatial indices. One hundred and five cross-sectional images from different species were transformed into binary images. The resulting point patterns, based on the locations of the conduit centers-of-area, were analyzed to determine whether they departed from randomness. Conduit distribution was then modeled using a spatially explicit stochastic model. * Key results: The presence of conduit randomness, uniformity, or aggregation depended on the spatial scale of the analysis. The large majority of the images showed patterns significantly different from randomness at least at one spatial scale. A strong phylogenetic signal was detected in the spatial variables. * Conclusions: Conduit spatial arrangement has been largely conserved during evolution, especially at small spatial scales. Species in which conduits were aggregated in clusters had a lower conduit density compared to those with uniform distribution. Statistically sound spatial indices must be employed as an aid in the characterization of distributional patterns across species and in models of xylem water transport. Point pattern analysis is a very useful tool in identifying spatial patterns.
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 IAM; Approved no
Call Number IAM @ iam @ MMG2010 Serial 1623
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Author Carolina Malagelada; Michal Drozdzal; Santiago Segui; Sara Mendez; Jordi Vitria; Petia Radeva; Javier Santos; Anna Accarino; Juan R. Malagelada; Fernando Azpiroz
Title Classification of functional bowel disorders by objective physiological criteria based on endoluminal image analysis Type Journal Article
Year 2015 Publication (up) American Journal of Physiology-Gastrointestinal and Liver Physiology Abbreviated Journal AJPGI
Volume 309 Issue 6 Pages G413--G419
Keywords capsule endoscopy; computer vision analysis; functional bowel disorders; intestinal motility; machine learning
Abstract We have previously developed an original method to evaluate small bowel motor function based on computer vision analysis of endoluminal images obtained by capsule endoscopy. Our aim was to demonstrate intestinal motor abnormalities in patients with functional bowel disorders by endoluminal vision analysis. Patients with functional bowel disorders (n = 205) and healthy subjects (n = 136) ingested the endoscopic capsule (Pillcam-SB2, Given-Imaging) after overnight fast and 45 min after gastric exit of the capsule a liquid meal (300 ml, 1 kcal/ml) was administered. Endoluminal image analysis was performed by computer vision and machine learning techniques to define the normal range and to identify clusters of abnormal function. After training the algorithm, we used 196 patients and 48 healthy subjects, completely naive, as test set. In the test set, 51 patients (26%) were detected outside the normal range (P < 0.001 vs. 3 healthy subjects) and clustered into hypo- and hyperdynamic subgroups compared with healthy subjects. Patients with hypodynamic behavior (n = 38) exhibited less luminal closure sequences (41 ± 2% of the recording time vs. 61 ± 2%; P < 0.001) and more static sequences (38 ± 3 vs. 20 ± 2%; P < 0.001); in contrast, patients with hyperdynamic behavior (n = 13) had an increased proportion of luminal closure sequences (73 ± 4 vs. 61 ± 2%; P = 0.029) and more high-motion sequences (3 ± 1 vs. 0.5 ± 0.1%; P < 0.001). Applying an original methodology, we have developed a novel classification of functional gut disorders based on objective, physiological criteria of small bowel function.
Address
Corporate Author Thesis
Publisher American Physiological Society 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; OR;MV Approved no
Call Number Admin @ si @ MDS2015 Serial 2666
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Author Sonia Baeza; R.Domingo; M.Salcedo; G.Moragas; J.Deportos; I.Garcia Olive; Carles Sanchez; Debora Gil; Antoni Rosell
Title Artificial Intelligence to Optimize Pulmonary Embolism Diagnosis During Covid-19 Pandemic by Perfusion SPECT/CT, a Pilot Study Type Journal Article
Year 2021 Publication (up) American Journal of Respiratory and Critical Care Medicine Abbreviated Journal
Volume Issue 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 Expedition Conference
Notes IAM; 600.145 Approved no
Call Number Admin @ si @ BDS2021 Serial 3591
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Author Henry Velesaca; Patricia Suarez; Angel Sappa; Dario Carpio; Rafael E. Rivadeneira; Angel Sanchez
Title Review on Common Techniques for Urban Environment Video Analytics Type Conference Article
Year 2022 Publication (up) Anais do III Workshop Brasileiro de Cidades Inteligentes Abbreviated Journal
Volume Issue Pages 107-118
Keywords Video Analytics; Review; Urban Environments; Smart Cities
Abstract This work compiles the different computer vision-based approaches
from the state-of-the-art intended for video analytics in urban environments.
The manuscript groups the different approaches according to the typical modules present in video analysis, including image preprocessing, object detection,
classification, and tracking. This proposed pipeline serves as a basic guide to
representing these most representative approaches in this topic of video analysis
that will be addressed in this work. Furthermore, the manuscript is not intended
to be an exhaustive review of the most advanced approaches, but only a list of
common techniques proposed to address recurring problems in this field.
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 WBCI
Notes MSIAU; 601.349 Approved no
Call Number Admin @ si @ VSS2022 Serial 3773
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Author D. Seron; F. Moreso; C. Gratin; Jordi Vitria; E. Condom
Title Automated classification of renal interstitium and tubules by local texture analysis and a neural network Type Journal Article
Year 1996 Publication (up) Analytical and Quantitative Cytology and Histology Abbreviated Journal
Volume 18 Issue 5 Pages 410-9, PMID: 8908314
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ SMG1996 Serial 76
Permanent link to this record
 
 
Author Petia Radeva
Title On the Role of Intravascular Ultrasound Image Analysis Type Miscellaneous
Year 2003 Publication (up) Angiography and Plaque Imaging: Advanced Segmentation Techniques, CRC, pp.397–450, ISBN: 0849317401 Abbreviated Journal
Volume Issue 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 Expedition Conference
Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ Rad2003 Serial 402
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Author J. Suri; S. Singh; S. Laxminarayan; R. Cesar; H. Jelinek; Petia Radeva; B. Roysam; Ch. Stewart; K. Frizche; J. Williams; H. Tek
Title A Note on Future Research in Vascular and Plaque Segmentation Type Miscellaneous
Year 2003 Publication (up) Angiography and Plaque Imaging: Advanced Segmentation Techniques, Editorial: CRC, pp.501–522, ISBN: 0849317401 Abbreviated Journal
Volume Issue 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 Expedition Conference
Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ SSL2003 Serial 419
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Author Jose Luis Alba; A. Pujol; Juan J. Villanueva
Title Novel SOM-PCA Network for Face Identification. Type Miscellaneous
Year 2001 Publication (up) Applications and Science of Neural Networks, Fuzzy Systems and Evolutonary Computation IV, SPIE´s International Symposium on Optical Science and Technology. Abbreviated Journal
Volume Issue 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 Expedition Conference
Notes Approved no
Call Number ISE @ ise @ APV2001a Serial 69
Permanent link to this record
 
 
Author Xavier Baro; Jordi Vitria
Title Evolutionary Object Detection by Means of Naive Bayes Models Estimation Type Book Chapter
Year 2008 Publication (up) Applications of Evolutionary Computing. EvoWorkshops Abbreviated Journal
Volume 4974 Issue Pages 235–244
Keywords
Abstract
Address Naples (Italy)
Corporate Author Thesis
Publisher Place of Publication Editor M. Giacobini
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes OR;HuPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ BaV2008a Serial 976
Permanent link to this record
 
 
Author Pau Rodriguez; Diego Velazquez; Guillem Cucurull; Josep M. Gonfaus; Xavier Roca; Seiichi Ozawa; Jordi Gonzalez
Title Personality Trait Analysis in Social Networks Based on Weakly Supervised Learning of Shared Images Type Journal Article
Year 2020 Publication (up) Applied Sciences Abbreviated Journal APPLSCI
Volume 10 Issue 22 Pages 8170
Keywords sentiment analysis, personality trait analysis; weakly-supervised learning; visual classification; OCEAN model; social networks
Abstract Social networks have attracted the attention of psychologists, as the behavior of users can be used to assess personality traits, and to detect sentiments and critical mental situations such as depression or suicidal tendencies. Recently, the increasing amount of image uploads to social networks has shifted the focus from text to image-based personality assessment. However, obtaining the ground-truth requires giving personality questionnaires to the users, making the process very costly and slow, and hindering research on large populations. In this paper, we demonstrate that it is possible to predict which images are most associated with each personality trait of the OCEAN personality model, without requiring ground-truth personality labels. Namely, we present a weakly supervised framework which shows that the personality scores obtained using specific images textually associated with particular personality traits are highly correlated with scores obtained using standard text-based personality questionnaires. We trained an OCEAN trait model based on Convolutional Neural Networks (CNNs), learned from 120K pictures posted with specific textual hashtags, to infer whether the personality scores from the images uploaded by users are consistent with those scores obtained from text. In order to validate our claims, we performed a personality test on a heterogeneous group of 280 human subjects, showing that our model successfully predicts which kind of image will match a person with a given level of a trait. Looking at the results, we obtained evidence that personality is not only correlated with text, but with image content too. Interestingly, different visual patterns emerged from those images most liked by persons with a particular personality trait: for instance, pictures most associated with high conscientiousness usually contained healthy food, while low conscientiousness pictures contained injuries, guns, and alcohol. These findings could pave the way to complement text-based personality questionnaires with image-based questions.
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 ISE; 600.119 Approved no
Call Number Admin @ si @ RVC2020b Serial 3553
Permanent link to this record