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Author Andrei Polzounov; Artsiom Ablavatski; Sergio Escalera; Shijian Lu; Jianfei Cai edit  openurl
  Title WordFences: Text Localization and Recognition Type Conference Article
  Year 2017 Publication 24th International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Beijing; China; September 2017  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICIP  
  Notes HUPBA; no menciona Approved no  
  Call Number Admin @ si @ PAE2017 Serial 3007  
Permanent link to this record
 

 
Author Sergio Escalera; Vassilis Athitsos; Isabelle Guyon edit  openurl
  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  
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  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 Jordi Esquirol; Cristina Palmero; Vanessa Bayo; Miquel Angel Cos; Sergio Escalera; David Sanchez; Maider Sanchez; Noelia Serrano; Mireia Relats edit  doi
openurl 
  Title Automatic RBG-depth-pressure anthropometric analysis and individualised sleep solution prescription Type Journal
  Year 2017 Publication Journal of Medical Engineering & Technology Abbreviated Journal JMET  
  Volume 41 Issue 6 Pages 486-497  
  Keywords  
  Abstract INTRODUCTION:
Sleep surfaces must adapt to individual somatotypic features to maintain a comfortable, convenient and healthy sleep, preventing diseases and injuries. Individually determining the most adequate rest surface can often be a complex and subjective question.
OBJECTIVES:
To design and validate an automatic multimodal somatotype determination model to automatically recommend an individually designed mattress-topper-pillow combination.
METHODS:
Design and validation of an automated prescription model for an individualised sleep system is performed through a single-image 2 D-3 D analysis and body pressure distribution, to objectively determine optimal individual sleep surfaces combining five different mattress densities, three different toppers and three cervical pillows.
RESULTS:
A final study (n = 151) and re-analysis (n = 117) defined and validated the model, showing high correlations between calculated and real data (>85% in height and body circumferences, 89.9% in weight, 80.4% in body mass index and more than 70% in morphotype categorisation).
CONCLUSIONS:
Somatotype determination model can accurately prescribe an individualised sleep solution. This can be useful for healthy people and for health centres that need to adapt sleep surfaces to people with special needs. Next steps will increase model's accuracy and analise, if this prescribed individualised sleep solution can improve sleep quantity and quality; additionally, future studies will adapt the model to mattresses with technological improvements, tailor-made production and will define interfaces for people with special needs.
 
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  Notes HUPBA; no menciona Approved no  
  Call Number Admin @ si @ EPB2017 Serial 3010  
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Author Sergio Escalera; Xavier Baro; Hugo Jair Escalante; Isabelle Guyon edit   pdf
openurl 
  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 (up)  
  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 Eirikur Agustsson; Radu Timofte; Sergio Escalera; Xavier Baro; Isabelle Guyon; Rasmus Rothe edit   pdf
doi  openurl
  Title Apparent and real age estimation in still images with deep residual regressors on APPA-REAL database Type Conference Article
  Year 2017 Publication 12th IEEE International Conference on Automatic Face and Gesture Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract After decades of research, the real (biological) age estimation from a single face image reached maturity thanks to the availability of large public face databases and impressive accuracies achieved by recently proposed methods.
The estimation of “apparent age” is a related task concerning the age perceived by human observers. Significant advances have been also made in this new research direction with the recent Looking At People challenges. In this paper we make several contributions to age estimation research. (i) We introduce APPA-REAL, a large face image database with both real and apparent age annotations. (ii) We study the relationship between real and apparent age. (iii) We develop a residual age regression method to further improve the performance. (iv) We show that real age estimation can be successfully tackled as an apparent age estimation followed by an apparent to real age residual regression. (v) We graphically reveal the facial regions on which the CNN focuses in order to perform apparent and real age estimation tasks.
 
  Address Washington;USA; May 2017  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference FG  
  Notes HUPBA; no menciona Approved no  
  Call Number Admin @ si @ ATE2017 Serial 3013  
Permanent link to this record
 

 
Author Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera; Huamin Ren; Thomas B. Moeslund; Elham Etemad edit  url
openurl 
  Title Locality Regularized Group Sparse Coding for Action Recognition Type Journal Article
  Year 2017 Publication Computer Vision and Image Understanding Abbreviated Journal CVIU  
  Volume 158 Issue Pages 106-114  
  Keywords Bag of words; Feature encoding; Locality constrained coding; Group sparse coding; Alternating direction method of multipliers; Action recognition  
  Abstract Bag of visual words (BoVW) models are widely utilized in image/ video representation and recognition. The cornerstone of these models is the encoding stage, in which local features are decomposed over a codebook in order to obtain a representation of features. In this paper, we propose a new encoding algorithm by jointly encoding the set of local descriptors of each sample and considering the locality structure of descriptors. The proposed method takes advantages of locality coding such as its stability and robustness to noise in descriptors, as well as the strengths of the group coding strategy by taking into account the potential relation among descriptors of a sample. To efficiently implement our proposed method, we consider the Alternating Direction Method of Multipliers (ADMM) framework, which results in quadratic complexity in the problem size. The method is employed for a challenging classification problem: action recognition by depth cameras. Experimental results demonstrate the outperformance of our methodology compared to the state-of-the-art on the considered datasets.  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes HuPBA; no proj Approved no  
  Call Number Admin @ si @ BGE2017 Serial 3014  
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Author Patricia Suarez; Angel Sappa; Boris X. Vintimilla edit   pdf
openurl 
  Title Colorizing Infrared Images through a Triplet Conditional DCGAN Architecture Type Conference Article
  Year 2017 Publication 19th international conference on image analysis and processing Abbreviated Journal  
  Volume Issue Pages  
  Keywords CNN in Multispectral Imaging; Image Colorization  
  Abstract This paper focuses on near infrared (NIR) image colorization by using a Conditional Deep Convolutional Generative Adversarial Network (CDCGAN) architecture model. The proposed architecture is based on the usage of a conditional probabilistic generative model. Firstly, it learns to colorize the given input image, by using a triplet model architecture that tackle every channel in an independent way. In the proposed model, the nal layer of red channel consider the infrared image to enhance the details, resulting in a sharp RGB image. Then, in the second stage, a discriminative model is used to estimate the probability that the generated image came from the training dataset, rather than the image automatically generated. Experimental results with a large set of real images are provided showing the validity of the proposed approach. Additionally, the proposed approach is compared with a state of the art approach showing better results.  
  Address Catania; Italy; September 2017  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICIAP  
  Notes ADAS; MSIAU; 600.086; 600.122; 600.118 Approved no  
  Call Number Admin @ si @ SSV2017c Serial 3016  
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Author Alejandro Cartas; Mariella Dimiccoli; Petia Radeva edit   pdf
url  openurl
  Title Batch-based activity recognition from egocentric photo-streams Type Conference Article
  Year 2017 Publication 1st International workshop on Egocentric Perception, Interaction and Computing Abbreviated Journal  
  Volume Issue Pages  
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  Abstract Activity recognition from long unstructured egocentric photo-streams has several applications in assistive technology such as health monitoring and frailty detection, just to name a few. However, one of its main technical challenges is to deal with the low frame rate of wearable photo-cameras, which causes abrupt appearance changes between consecutive frames. In consequence, important discriminatory low-level features from motion such as optical flow cannot be estimated. In this paper, we present a batch-driven approach for training a deep learning architecture that strongly rely on Long short-term units to tackle this problem. We propose two different implementations of the same approach that process a photo-stream sequence using batches of fixed size with the goal of capturing the temporal evolution of high-level features. The main difference between these implementations is that one explicitly models consecutive batches by overlapping them. Experimental results over a public dataset acquired by three users demonstrate the validity of the proposed architectures to exploit the temporal evolution of convolutional features over time without relying on event boundaries.  
  Address Venice; Italy; October 2017;  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference ICCV - EPIC  
  Notes MILAB; no menciona Approved no  
  Call Number Admin @ si @ CDR2017 Serial 3023  
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Author Aniol Lidon; Marc Bolaños; Mariella Dimiccoli; Petia Radeva; Maite Garolera; Xavier Giro edit   pdf
doi  isbn
openurl 
  Title Semantic Summarization of Egocentric Photo-Stream Events Type Conference Article
  Year 2017 Publication 2nd Workshop on Lifelogging Tools and Applications Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address San Francisco; USA; October 2017  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4503-5503-2 Medium  
  Area Expedition Conference ACMW (LTA)  
  Notes MILAB; no proj Approved no  
  Call Number Admin @ si @ LBD2017 Serial 3024  
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Author Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva edit   pdf
openurl 
  Title All the people around me: face clustering in egocentric photo streams Type Conference Article
  Year 2017 Publication 24th International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages  
  Keywords face discovery; face clustering; deepmatching; bag-of-tracklets; egocentric photo-streams  
  Abstract arxiv1703.01790
Given an unconstrained stream of images captured by a wearable photo-camera (2fpm), we propose an unsupervised bottom-up approach for automatic clustering appearing faces into the individual identities present in these data. The problem is challenging since images are acquired under real world conditions; hence the visible appearance of the people in the images undergoes intensive variations. Our proposed pipeline consists of first arranging the photo-stream into events, later, localizing the appearance of multiple people in them, and
finally, grouping various appearances of the same person across different events. Experimental results performed on a dataset acquired by wearing a photo-camera during one month, demonstrate the effectiveness of the proposed approach for the considered purpose.
 
  Address Beijing; China; September 2017  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICIP  
  Notes MILAB; no menciona Approved no  
  Call Number Admin @ si @ EDR2017 Serial 3025  
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Author Laura Igual; Santiago Segui edit  isbn
openurl 
  Title Introduction to Data Science – A Python Approach to Concepts, Techniques and Applications. Undergraduate Topics in Computer Science Type Book Whole
  Year 2017 Publication Abbreviated Journal  
  Volume Issue Pages 1-215  
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  Abstract  
  Address  
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  Publisher 978-3-319-50016-4 Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-319-50016-4 Medium  
  Area Expedition Conference  
  Notes MILAB Approved no  
  Call Number Admin @ si @ IgS2017 Serial 3027  
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Author Mireia Forns-Nadal; Federico Sem; Anna Mane; Laura Igual; Dani Guinart; Oscar Vilarroya edit  url
doi  openurl
  Title Increased Nucleus Accumbens Volume in First-Episode Psychosis Type Journal Article
  Year 2017 Publication Psychiatry Research-Neuroimaging Abbreviated Journal PRN  
  Volume 263 Issue Pages 57-60  
  Keywords  
  Abstract Nucleus accumbens has been reported as a key structure in the neurobiology of schizophrenia. Studies analyzing structural abnormalities have shown conflicting results, possibly related to confounding factors. We investigated the nucleus accumbens volume using manual delimitation in first-episode psychosis (FEP) controlling for age, cannabis use and medication. Thirty-one FEP subjects who were naive or minimally exposed to antipsychotics and a control group were MRI scanned and clinically assessed from baseline to 6 months of follow-up. FEP showed increased relative and total accumbens volumes. Clinical correlations with negative symptoms, duration of untreated psychosis and cannabis use were not significant.  
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  Series Editor Series Title Abbreviated Series Title  
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  Area Expedition Conference  
  Notes MILAB; no menciona Approved no  
  Call Number Admin @ si @ FSM2017 Serial 3028  
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Author Fernando Vilariño; Dan Norton edit  openurl
  Title Using mutimedia tools to spread poetry collections Type Conference Article
  Year 2017 Publication Internet librarian International Conference Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address London; UK; October 2017  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ILI  
  Notes MV; 600.097;SIAI Approved no  
  Call Number Admin @ si @ ViN2017 Serial 3031  
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Author Fernando Vilariño edit  openurl
  Title Citizen experience as a powerful communication tool: Open Innovation and the role of Living Labs in EU Type Conference Article
  Year 2017 Publication European Conference of Science Journalists Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract The Open Innovation 2.0 model spearheaded by the European Commission introduces conceptual changes in how innovation processes should be developed. The notion of an innovation ecosystem, and the active participation of the citizens (and all the different actors of the quadruple helix) in innovation processes, opens up new channels for scientific communication, where the citizens (and all actors) can be naturally reached and facilitate the spread of the scientific message in their communities. Unleashing the power of such mechanisms, while maintaining control over the scientific communication done through such channels presents an opportunity and a challenge at the same time.

This workshop will look into key concepts that the Open Innovation 2.0 EU model introduces, and what new opportunities for communication they bring about. Specifically, we will focus on Living Labs, as a key instrument for implementing this innovation model at the regional level, and their potential in creating scientific dissemination spaces.
 
  Address Copenhagen; June 2017  
  Corporate Author Thesis  
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  ISSN ISBN Medium  
  Area Expedition Conference ECSJ  
  Notes MV; 600.097;SIAI Approved no  
  Call Number Admin @ si @ Vil2017a Serial 3032  
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Author Fernando Vilariño edit  openurl
  Title Bringing and keeping all the stakeholders together: creating a catalog of models of governance for innovation Type Miscellaneous
  Year 2017 Publication Open Living Lab Days Report Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Krakow; August 2017  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MV; no menciona;SIAI Approved no  
  Call Number Admin @ si @ Vil2017b Serial 3033  
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