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Author Asma Bensalah; Alicia Fornes; Cristina Carmona_Duarte; Josep Llados
Title Easing Automatic Neurorehabilitation via Classification and Smoothness Analysis Type Conference Article
Year 2022 Publication Intertwining Graphonomics with Human Movements. 20th International Conference of the International Graphonomics Society, IGS 2022 Abbreviated Journal
Volume 13424 Issue Pages 336-348
Keywords Neurorehabilitation; Upper-lim; Movement classification; Movement smoothness; Deep learning; Jerk
Abstract Assessing the quality of movements for post-stroke patients during the rehabilitation phase is vital given that there is no standard stroke rehabilitation plan for all the patients. In fact, it depends basically on the patient’s functional independence and its progress along the rehabilitation sessions. To tackle this challenge and make neurorehabilitation more agile, we propose an automatic assessment pipeline that starts by recognising patients’ movements by means of a shallow deep learning architecture, then measuring the movement quality using jerk measure and related measures. A particularity of this work is that the dataset used is clinically relevant, since it represents movements inspired from Fugl-Meyer a well common upper-limb clinical stroke assessment scale for stroke patients. We show that it is possible to detect the contrast between healthy and patients movements in terms of smoothness, besides achieving conclusions about the patients’ progress during the rehabilitation sessions that correspond to the clinicians’ findings about each case.
Address (up) June 7-9, 2022, 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 LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference IGS
Notes DAG; 600.121; 600.162; 602.230; 600.140 Approved no
Call Number Admin @ si @ BFC2022 Serial 3738
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Author Alicia Fornes; Asma Bensalah; Cristina Carmona_Duarte; Jialuo Chen; Miguel A. Ferrer; Andreas Fischer; Josep Llados; Cristina Martin; Eloy Opisso; Rejean Plamondon; Anna Scius-Bertrand; Josep Maria Tormos
Title The RPM3D Project: 3D Kinematics for Remote Patient Monitoring Type Conference Article
Year 2022 Publication Intertwining Graphonomics with Human Movements. 20th International Conference of the International Graphonomics Society, IGS 2022 Abbreviated Journal
Volume 13424 Issue Pages 217-226
Keywords Healthcare applications; Kinematic; Theory of Rapid Human Movements; Human activity recognition; Stroke rehabilitation; 3D kinematics
Abstract This project explores the feasibility of remote patient monitoring based on the analysis of 3D movements captured with smartwatches. We base our analysis on the Kinematic Theory of Rapid Human Movement. We have validated our research in a real case scenario for stroke rehabilitation at the Guttmann Institute (https://www.guttmann.com/en/) (neurorehabilitation hospital), showing promising results. Our work could have a great impact in remote healthcare applications, improving the medical efficiency and reducing the healthcare costs. Future steps include more clinical validation, developing multi-modal analysis architectures (analysing data from sensors, images, audio, etc.), and exploring the application of our technology to monitor other neurodegenerative diseases.
Address (up) June 7-9, 2022, 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 LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference IGS
Notes DAG; 600.121; 600.162; 602.230; 600.140 Approved no
Call Number Admin @ si @ FBC2022 Serial 3739
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Author German Ros; J. Guerrero; Angel Sappa; Antonio Lopez
Title VSLAM pose initialization via Lie groups and Lie algebras optimization Type Conference Article
Year 2013 Publication Proceedings of IEEE International Conference on Robotics and Automation Abbreviated Journal
Volume Issue Pages 5740 - 5747
Keywords SLAM
Abstract We present a novel technique for estimating initial 3D poses in the context of localization and Visual SLAM problems. The presented approach can deal with noise, outliers and a large amount of input data and still performs in real time in a standard CPU. Our method produces solutions with an accuracy comparable to those produced by RANSAC but can be much faster when the percentage of outliers is high or for large amounts of input data. On the current work we propose to formulate the pose estimation as an optimization problem on Lie groups, considering their manifold structure as well as their associated Lie algebras. This allows us to perform a fast and simple optimization at the same time that conserve all the constraints imposed by the Lie group SE(3). Additionally, we present several key design concepts related with the cost function and its Jacobian; aspects that are critical for the good performance of the algorithm.
Address (up) Karlsruhe; Germany; May 2013
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 1050-4729 ISBN 978-1-4673-5641-1 Medium
Area Expedition Conference ICRA
Notes ADAS; 600.054; 600.055; 600.057 Approved no
Call Number Admin @ si @ RGS2013a; ADAS @ adas @ Serial 2225
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Author Sergio Escalera; Jordi Gonzalez; Xavier Baro; Pablo Pardo; Junior Fabian; Marc Oliu; Hugo Jair Escalante; Ivan Huerta; Isabelle Guyon
Title ChaLearn Looking at People 2015 new competitions: Age Estimation and Cultural Event Recognition Type Conference Article
Year 2015 Publication IEEE International Joint Conference on Neural Networks IJCNN2015 Abbreviated Journal
Volume Issue Pages 1-8
Keywords
Abstract Following previous series on Looking at People (LAP) challenges [1], [2], [3], in 2015 ChaLearn runs two new competitions within the field of Looking at People: age and cultural event recognition in still images. We propose thefirst crowdsourcing application to collect and label data about apparent
age of people instead of the real age. In terms of cultural event recognition, tens of categories have to be recognized. This involves scene understanding and human analysis. This paper summarizes both challenges and data, providing some initial baselines. The results of the first round of the competition were presented at ChaLearn LAP 2015 IJCNN special session on computer vision and robotics http://www.dtic.ua.es/∼jgarcia/IJCNN2015.
Details of the ChaLearn LAP competitions can be found at http://gesture.chalearn.org/.
Address (up) Killarney; Ireland; July 2015
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; ISE; 600.063; 600.078;MV Approved no
Call Number Admin @ si @ EGB2015 Serial 2591
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Author Hugo Jair Escalante; Jose Martinez; Sergio Escalera; Victor Ponce; Xavier Baro
Title Improving Bag of Visual Words Representations with Genetic Programming Type Conference Article
Year 2015 Publication IEEE International Joint Conference on Neural Networks IJCNN2015 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract The bag of visual words is a well established representation in diverse computer vision problems. Taking inspiration from the fields of text mining and retrieval, this representation has proved to be very effective in a large number of domains.
In most cases, a standard term-frequency weighting scheme is considered for representing images and videos in computer vision. This is somewhat surprising, as there are many alternative ways of generating bag of words representations within the text processing community. This paper explores the use of alternative weighting schemes for landmark tasks in computer vision: image
categorization and gesture recognition. We study the suitability of using well-known supervised and unsupervised weighting schemes for such tasks. More importantly, we devise a genetic program that learns new ways of representing images and videos under the bag of visual words representation. The proposed method learns to combine term-weighting primitives trying to maximize the classification performance. Experimental results are reported in standard image and video data sets showing the effectiveness of the proposed evolutionary algorithm.
Address (up) Killarney; Ireland; July 2015
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;MV Approved no
Call Number Admin @ si @ EME2015 Serial 2603
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Author Isabelle Guyon; Kristin Bennett; Gavin Cawley; Hugo Jair Escalante; Sergio Escalera; Tin Kam Ho; Nuria Macia; Bisakha Ray; Alexander Statnikov; Evelyne Viegas
Title Design of the 2015 ChaLearn AutoML Challenge Type Conference Article
Year 2015 Publication IEEE International Joint Conference on Neural Networks IJCNN2015 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract ChaLearn is organizing for IJCNN 2015 an Automatic Machine Learning challenge (AutoML) to solve classification and regression problems from given feature representations, without any human intervention. This is a challenge with code
submission: the code submitted can be executed automatically on the challenge servers to train and test learning machines on new datasets. However, there is no obligation to submit code. Half of the prizes can be won by just submitting prediction results.
There are six rounds (Prep, Novice, Intermediate, Advanced, Expert, and Master) in which datasets of progressive difficulty are introduced (5 per round). There is no requirement to participate in previous rounds to enter a new round. The rounds alternate AutoML phases in which submitted code is “blind tested” on
datasets the participants have never seen before, and Tweakathon phases giving time (' 1 month) to the participants to improve their methods by tweaking their code on those datasets. This challenge will push the state-of-the-art in fully automatic machine learning on a wide range of problems taken from real world
applications. The platform will remain available beyond the termination of the challenge: http://codalab.org/AutoML
Address (up) Killarney; Ireland; July 2015
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;MILAB Approved no
Call Number Admin @ si @ GBC2015a Serial 2604
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Author Isabelle Guyon; Kristin Bennett; Gavin Cawley; Hugo Jair Escalante; Sergio Escalera
Title The AutoML challenge on codalab Type Conference Article
Year 2015 Publication IEEE International Joint Conference on Neural Networks IJCNN2015 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address (up) Killarney; Ireland; July 2015
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;MILAB Approved no
Call Number Admin @ si @ GBC2015b Serial 2650
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Author Gerard Canal; Cecilio Angulo; Sergio Escalera
Title Gesture based Human Multi-Robot interaction Type Conference Article
Year 2015 Publication IEEE International Joint Conference on Neural Networks IJCNN2015 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract The emergence of robot applications for nontechnical users implies designing new ways of interaction between robotic platforms and users. The main goal of this work is the development of a gestural interface to interact with robots
in a similar way as humans do, allowing the user to provide information of the task with non-verbal communication. The gesture recognition application has been implemented using the Microsoft’s KinectTM v2 sensor. Hence, a real-time algorithm based on skeletal features is described to deal with both, static
gestures and dynamic ones, being the latter recognized using a weighted Dynamic Time Warping method. The gesture recognition application has been implemented in a multi-robot case.

A NAO humanoid robot is in charge of interacting with the users and respond to the visual signals they produce. Moreover, a wheeled Wifibot robot carries both the sensor and the NAO robot, easing navigation when necessary. A broad set of user tests have been carried out demonstrating that the system is, indeed, a
natural approach to human robot interaction, with a fast response and easy to use, showing high gesture recognition rates.
Address (up) Killarney; Ireland; July 2015
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;MILAB Approved no
Call Number CAE2015a Serial 2651
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Author Partha Pratim Roy; Josep Llados; Umapada Pal
Title Text/Graphics Separation in Color Maps Type Conference Article
Year 2007 Publication International Conference on Computing: Theory and Applications Abbreviated Journal
Volume Issue Pages 545–551
Keywords
Abstract
Address (up) Kolkata (India)
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 ICCTA
Notes DAG Approved no
Call Number DAG @ dag @ RLP2007a Serial 806
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Author Oriol Ramos Terrades; Salvatore Tabbone; Ernest Valveny
Title Optimal Linear Combination for Two-class Classifiers Type Conference Article
Year 2007 Publication Proceedings of the International Conference on Advances in Pattern Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address (up) Kolkata (India)
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 ICAPR
Notes DAG Approved no
Call Number DAG @ dag @ RTV2007a Serial 894
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Author Alicia Fornes; Josep Llados
Title A Symbol-dependent Writer Identifcation Approach in Old Handwritten Music Scores Type Conference Article
Year 2010 Publication 12th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal
Volume Issue Pages 634 - 639
Keywords
Abstract Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we introduce a symbol-dependent approach for identifying the writer of old music scores, which is based on two symbol recognition methods. The main idea is to use the Blurred Shape Model descriptor and a DTW-based method for detecting, recognizing and describing the music clefs and notes. The proposed approach has been evaluated in a database of old music scores, achieving very high writer identification rates.
Address (up) Kolkata (India)
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 978-1-4244-8353-2 Medium
Area Expedition Conference ICFHR
Notes DAG Approved no
Call Number DAG @ dag @ FoL2010 Serial 1321
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Author Fernando Vilariño
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
Keywords
Abstract
Address (up) Krakow; 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 Medium
Area Expedition Conference
Notes MV; no menciona;SIAI Approved no
Call Number Admin @ si @ Vil2017b Serial 3033
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Author Zhong Jin; Franck Davoine
Title Orthogonal ICA Representation Of Images Type Miscellaneous
Year 2004 Publication 8th International Conference on Control, Automation, Robotics and Vision, 369–374 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address (up) Kunming (China)
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 Admin @ si @ JiD2004 Serial 499
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Author Xavier Boix; Josep M. Gonfaus; Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Marco Pedersoli; Jordi Gonzalez; Joan Serrat
Title Combining local and global bag-of-word representations for semantic segmentation Type Conference Article
Year 2009 Publication Workshop on The PASCAL Visual Object Classes Challenge Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address (up) Kyoto (Japan)
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 ICCV
Notes ADAS;ISE Approved no
Call Number ADAS @ adas @ BGS2009 Serial 1273
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Author Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell
Title Top-Down Color Attention for Object Recognition Type Conference Article
Year 2009 Publication 12th International Conference on Computer Vision Abbreviated Journal
Volume Issue Pages 979 - 986
Keywords
Abstract Generally the bag-of-words based image representation follows a bottom-up paradigm. The subsequent stages of the process: feature detection, feature description, vocabulary construction and image representation are performed independent of the intentioned object classes to be detected. In such a framework, combining multiple cues such as shape and color often provides below-expected results. This paper presents a novel method for recognizing object categories when using multiple cues by separating the shape and color cue. Color is used to guide attention by means of a top-down category-specific attention map. The color attention map is then further deployed to modulate the shape features by taking more features from regions within an image that are likely to contain an object instance. This procedure leads to a category-specific image histogram representation for each category. Furthermore, we argue that the method combines the advantages of both early and late fusion. We compare our approach with existing methods that combine color and shape cues on three data sets containing varied importance of both cues, namely, Soccer ( color predominance), Flower (color and shape parity), and PASCAL VOC Challenge 2007 (shape predominance). The experiments clearly demonstrate that in all three data sets our proposed framework significantly outperforms the state-of-the-art methods for combining color and shape information.
Address (up) Kyoto, Japan
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 1550-5499 ISBN 978-1-4244-4420-5 Medium
Area Expedition Conference ICCV
Notes CIC Approved no
Call Number CAT @ cat @ SWV2009 Serial 1196
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