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Author (down) Sounak Dey; Anjan Dutta; Josep Llados; Alicia Fornes; Umapada Pal
Title Shallow Neural Network Model for Hand-drawn Symbol Recognition in Multi-Writer Scenario Type Conference Article
Year 2017 Publication 12th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages 31-32
Keywords
Abstract One of the main challenges in hand drawn symbol recognition is the variability among symbols because of the different writer styles. In this paper, we present and discuss some results recognizing hand-drawn symbols with a shallow neural network. A neural network model inspired from the LeNet architecture has been used to achieve state-of-the-art results with
very less training data, which is very unlikely to the data hungry deep neural network. From the results, it has become evident that the neural network architectures can efficiently describe and recognize hand drawn symbols from different writers and can model the inter author aberration
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 GREC
Notes DAG; 600.097; 600.121 Approved no
Call Number Admin @ si @ DDL2017 Serial 3057
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Author (down) Simone Balocco; Francesco Ciompi; Juan Rigla; Xavier Carrillo; J. Mauri; Petia Radeva
Title Intra-Coronary Stent localization In Intravascular Ultrasound Sequences, A Preliminary Study Type Conference Article
Year 2017 Publication International workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting (CVII-STENT) Abbreviated Journal
Volume Issue Pages
Keywords
Abstract An intraluminal coronary stent is a metal scaold deployed in a stenotic artery during Percutaneous Coronary Intervention (PCI).
Intravascular Ultrasound (IVUS) is a catheter-based imaging technique generally used for assessing the correct placement of the stent. All the approaches proposed so far for the stent analysis only focused on the struts detection, while this paper proposes a novel approach to detect the boundaries and the position of the stent along the pullback.
The pipeline of the method requires the identication of the stable frames
of the sequence and the reliable detection of stent struts. Using this data,
a measure of likelihood for a frame to contain a stent is computed. Then,
a robust binary representation of the presence of the stent in the pullback
is obtained applying an iterative and multi-scale approximation of the signal to symbols using the SAX algorithm. Results obtained comparing the automatic results versus the manual annotation of two observers on 80 IVUS in-vivo sequences shows that the method approaches the inter-observer variability scores.
Address Quebec; Canada; September 2017
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 MICCAIW
Notes MILAB; no proj Approved no
Call Number Admin @ si @ BCR2017 Serial 2968
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Author (down) Simon Jégou; Michal Drozdzal; David Vazquez; Adriana Romero; Yoshua Bengio
Title The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation Type Conference Article
Year 2017 Publication IEEE Conference on Computer Vision and Pattern Recognition Workshops Abbreviated Journal
Volume Issue Pages
Keywords Semantic Segmentation
Abstract State-of-the-art approaches for semantic image segmentation are built on Convolutional Neural Networks (CNNs). The typical segmentation architecture is composed of (a) a downsampling path responsible for extracting coarse semantic features, followed by (b) an upsampling path trained to recover the input image resolution at the output of the model and, optionally, (c) a post-processing module (e.g. Conditional Random Fields) to refine the model predictions.

Recently, a new CNN architecture, Densely Connected Convolutional Networks (DenseNets), has shown excellent results on image classification tasks. The idea of DenseNets is based on the observation that if each layer is directly connected to every other layer in a feed-forward fashion then the network will be more accurate and easier to train.

In this paper, we extend DenseNets to deal with the problem of semantic segmentation. We achieve state-of-the-art results on urban scene benchmark datasets such as CamVid and Gatech, without any further post-processing module nor pretraining. Moreover, due to smart construction of the model, our approach has much less parameters than currently published best entries for these datasets.
Address Honolulu; USA; July 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 CVPRW
Notes MILAB; ADAS; 600.076; 600.085; 601.281 Approved no
Call Number ADAS @ adas @ JDV2016 Serial 2866
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Author (down) Sergio Escalera; Xavier Baro; Hugo Jair Escalante; Isabelle Guyon
Title ChaLearn Looking at People: A Review of Events and Resources Type Conference Article
Year 2017 Publication 30th International Joint Conference on Neural Networks Abbreviated Journal
Volume Issue Pages
Keywords
Abstract This paper reviews the historic of ChaLearn Looking at People (LAP) events. We started in 2011 (with the release of the first Kinect device) to run challenges related to human action/activity and gesture recognition. Since then we have regularly organized events in a series of competitions covering all aspects of visual analysis of humans. So far we have organized more than 10 international challenges and events in this field. This paper reviews associated events, and introduces the ChaLearn LAP platform where public resources (including code, data and preprints of papers) related to the organized events are available. We also provide a discussion on perspectives of ChaLearn LAP activities.
Address Anchorage; Alaska; USA; May 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 IJCNN
Notes HuPBA; 602.143 Approved no
Call Number Admin @ si @ EBE2017 Serial 3012
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Author (down) Sergio Escalera; Vassilis Athitsos; Isabelle Guyon
Title Challenges in Multi-modal Gesture Recognition Type Book Chapter
Year 2017 Publication Abbreviated Journal
Volume Issue Pages 1-60
Keywords Gesture recognition; Time series analysis; Multimodal data analysis; Computer vision; Pattern recognition; Wearable sensors; Infrared cameras; Kinect TMTM
Abstract This paper surveys the state of the art on multimodal gesture recognition and introduces the JMLR special topic on gesture recognition 2011–2015. We began right at the start of the Kinect TMTM revolution when inexpensive infrared cameras providing image depth recordings became available. We published papers using this technology and other more conventional methods, including regular video cameras, to record data, thus providing a good overview of uses of machine learning and computer vision using multimodal data in this area of application. Notably, we organized a series of challenges and made available several datasets we recorded for that purpose, including tens of thousands of videos, which are available to conduct further research. We also overview recent state of the art works on gesture recognition based on a proposed taxonomy for gesture recognition, discussing challenges and future lines of research.
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; no proj Approved no
Call Number Admin @ si @ EAG2017 Serial 3008
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Author (down) 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 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 (down) Rosa Maria Ortiz; Debora Gil; Elisa Minchole; Marta Diez-Ferrer; Noelia Cubero de Frutos
Title Classification of Confolcal Endomicroscopy Patterns for Diagnosis of Lung Cancer Type Conference Article
Year 2017 Publication 18th World Conference on Lung Cancer Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Confocal Laser Endomicroscopy (CLE) is an emerging imaging technique that allows the in-vivo acquisition of cell patterns of potentially malignant lesions. Such patterns could discriminate between inflammatory and neoplastic lesions and, thus, serve as a first in-vivo biopsy to discard cases that do not actually require a cell biopsy.

The goal of this work is to explore whether CLE images obtained during videobronchoscopy contain enough visual information to discriminate between benign and malign peripheral lesions for lung cancer diagnosis. To do so, we have performed a pilot comparative study with 12 patients (6 adenocarcinoma and 6 benign-inflammatory) using 2 different methods for CLE pattern analysis: visual analysis by 3 experts and a novel methodology that uses graph methods to find patterns in pre-trained feature spaces. Our preliminary results indicate that although visual analysis can only achieve a 60.2% of accuracy, the accuracy of the proposed unsupervised image pattern classification raises to 84.6%.

We conclude that CLE images visual information allow in-vivo detection of neoplastic lesions and graph structural analysis applied to deep-learning feature spaces can achieve competitive results.
Address Yokohama; Japan; October 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 IASLC WCLC
Notes IAM; 600.096; 600.075; 600.145 Approved no
Call Number Admin @ si @ OGM2017 Serial 3044
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Author (down) Raul Gomez; Baoguang Shi; Lluis Gomez; Lukas Numann; Andreas Veit; Jiri Matas; Serge Belongie; Dimosthenis Karatzas
Title ICDAR2017 Robust Reading Challenge on COCO-Text Type Conference Article
Year 2017 Publication 14th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Kyoto; Japan; November 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 ICDAR
Notes DAG; 600.121 Approved no
Call Number Admin @ si @ GSG2017 Serial 3076
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Author (down) Rada Deeb; Damien Muselet; Mathieu Hebert; Alain Tremeau; Joost Van de Weijer
Title 3D color charts for camera spectral sensitivity estimation Type Conference Article
Year 2017 Publication 28th British Machine Vision Conference Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Estimating spectral data such as camera sensor responses or illuminant spectral power distribution from raw RGB camera outputs is crucial in many computer vision applications.
Usually, 2D color charts with various patches of known spectral reflectance are
used as reference for such purpose. Deducing n-D spectral data (n»3) from 3D RGB inputs is an ill-posed problem that requires a high number of inputs. Unfortunately, most of the natural color surfaces have spectral reflectances that are well described by low-dimensional linear models, i.e. each spectral reflectance can be approximated by a weighted sum of the others. It has been shown that adding patches to color charts does not help in practice, because the information they add is redundant with the information provided by the first set of patches. In this paper, we propose to use spectral data of
higher dimensionality by using 3D color charts that create inter-reflections between the surfaces. These inter-reflections produce multiplications between natural spectral curves and so provide non-linear spectral curves. We show that such data provide enough information for accurate spectral data estimation.
Address London; September 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 BMVC
Notes LAMP; 600.109; 600.120 Approved no
Call Number Admin @ si @ DMH2017b Serial 3037
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Author (down) Quentin Angermann; Jorge Bernal; Cristina Sanchez Montes; Maroua Hammami; Gloria Fernandez Esparrach; Xavier Dray; Olivier Romain; F. Javier Sanchez; Aymeric Histace
Title Real-Time Polyp Detection in Colonoscopy Videos: A Preliminary Study For Adapting Still Frame-based Methodology To Video Sequences Analysis Type Conference Article
Year 2017 Publication 31st International Congress and Exhibition on Computer Assisted Radiology and Surgery Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Barcelona; Spain; 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 CARS
Notes MV; no menciona Approved no
Call Number Admin @ si @ ABS2017 Serial 2947
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Author (down) Quentin Angermann; Jorge Bernal; Cristina Sanchez Montes; Maroua Hammami; Gloria Fernandez Esparrach; Xavier Dray; Olivier Romain; F. Javier Sanchez; Aymeric Histace
Title Clinical Usability Quantification Of a Real-Time Polyp Detection Method In Videocolonoscopy Type Conference Article
Year 2017 Publication 25th United European Gastroenterology Week Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Barcelona, October 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 ESGE
Notes MV; no menciona Approved no
Call Number Admin @ si @ ABS2017c Serial 2978
Permanent link to this record
 
 
Author (down) Quentin Angermann; Jorge Bernal; Cristina Sanchez Montes; Gloria Fernandez Esparrach; Xavier Gray; Olivier Romain; F. Javier Sanchez; Aymeric Histace
Title Towards Real-Time Polyp Detection in Colonoscopy Videos: Adapting Still Frame-Based Methodologies for Video Sequences Analysis Type Conference Article
Year 2017 Publication 4th International Workshop on Computer Assisted and Robotic Endoscopy Abbreviated Journal
Volume Issue Pages 29-41
Keywords Polyp detection; colonoscopy; real time; spatio temporal coherence
Abstract Colorectal cancer is the second cause of cancer death in United States: precursor lesions (polyps) detection is key for patient survival. Though colonoscopy is the gold standard screening tool, some polyps are still missed. Several computational systems have been proposed but none of them are used in the clinical room mainly due to computational constraints. Besides, most of them are built over still frame databases, decreasing their performance on video analysis due to the lack of output stability and not coping with associated variability on image quality and polyp appearance. We propose a strategy to adapt these methods to video analysis by adding a spatio-temporal stability module and studying a combination of features to capture polyp appearance variability. We validate our strategy, incorporated on a real-time detection method, on a public video database. Resulting method detects all
polyps under real time constraints, increasing its performance due to our
adaptation strategy.
Address Quebec; Canada; September 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 CARE
Notes MV; 600.096; 600.075 Approved no
Call Number Admin @ si @ ABS2017b Serial 2977
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Author (down) Pierdomenico Fiadino; Victor Ponce; Juan Antonio Torrero-Gonzalez; Marc Torrent-Moreno
Title Call Detail Records for Human Mobility Studies: Taking Stock of the Situation in the “Always Connected Era" Type Conference Article
Year 2017 Publication Workshop on Big Data Analytics and Machine Learning for Data Communication Networks Abbreviated Journal
Volume Issue Pages 43-48
Keywords mobile networks; call detail records; human mobility
Abstract The exploitation of cellular network data for studying human mobility has been a popular research topic in the last decade. Indeed, mobile terminals could be considered ubiquitous sensors that allow the observation of human movements on large scale without the need of relying on non-scalable techniques, such as surveys, or dedicated and expensive monitoring infrastructures. In particular, Call Detail Records (CDRs), collected by operators for billing purposes,
have been extensively employed due to their rather large availability, compared to other types of cellular data (e.g., signaling). Despite the interest aroused around this topic, the research community has generally agreed about the scarcity of information provided by CDRs: the position of mobile terminals is logged when some kind of activity (calls, SMS, data connections) occurs, which translates in a picture of mobility somehow biased by the activity degree of users.
By studying two datasets collected by a Nation-wide operator in 2014 and 2016, we show that the situation has drastically changed in terms of data volume and quality. The increase of flat data plans and the higher penetration of “
always connected” terminals have driven up the number of recorded CDRs, providing higher temporal accuracy for users’ locations.
Address UCLA; USA; August 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 978-1-4503-5054-9 Medium
Area Expedition Conference ACMW (SIGCOMM)
Notes HuPBA; no menciona Approved no
Call Number Admin @ si @ FPT2017 Serial 2980
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Author (down) Pau Rodriguez; Jordi Gonzalez; Jordi Cucurull; Josep M. Gonfaus; Xavier Roca
Title Regularizing CNNs with Locally Constrained Decorrelations Type Conference Article
Year 2017 Publication 5th International Conference on Learning Representations Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Toulon; France; April 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 ICLR
Notes ISE; 602.143; 600.119; 600.098 Approved no
Call Number Admin @ si @ RGC2017 Serial 2927
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Author (down) Pau Rodriguez; Guillem Cucurull; Josep M. Gonfaus; Xavier Roca; Jordi Gonzalez
Title Age and gender recognition in the wild with deep attention Type Journal Article
Year 2017 Publication Pattern Recognition Abbreviated Journal PR
Volume 72 Issue Pages 563-571
Keywords Age recognition; Gender recognition; Deep neural networks; Attention mechanisms
Abstract Face analysis in images in the wild still pose a challenge for automatic age and gender recognition tasks, mainly due to their high variability in resolution, deformation, and occlusion. Although the performance has highly increased thanks to Convolutional Neural Networks (CNNs), it is still far from optimal when compared to other image recognition tasks, mainly because of the high sensitiveness of CNNs to facial variations. In this paper, inspired by biology and the recent success of attention mechanisms on visual question answering and fine-grained recognition, we propose a novel feedforward attention mechanism that is able to discover the most informative and reliable parts of a given face for improving age and gender classification. In particular, given a downsampled facial image, the proposed model is trained based on a novel end-to-end learning framework to extract the most discriminative patches from the original high-resolution image. Experimental validation on the standard Adience, Images of Groups, and MORPH II benchmarks show that including attention mechanisms enhances the performance of CNNs in terms of robustness and accuracy.
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; 600.098; 602.133; 600.119 Approved no
Call Number Admin @ si @ RCG2017b Serial 2962
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