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Author Hans Stadthagen-Gonzalez; Luis Lopez; M. Carmen Parafita; C. Alejandro Parraga
Title Using two-alternative forced choice tasks and Thurstone law of comparative judgments for code-switching research Type Book Chapter
Year 2018 Publication Linguistic Approaches to Bilingualism Abbreviated Journal
Volume Issue Pages 67-97
Keywords (up) two-alternative forced choice and Thurstone's law; acceptability judgment; code-switching
Abstract This article argues that 2-alternative forced choice tasks and Thurstone’s law of comparative judgments (Thurstone, 1927) are well suited to investigate code-switching competence by means of acceptability judgments. We compare this method with commonly used Likert scale judgments and find that the 2-alternative forced choice task provides granular details that remain invisible in a Likert scale experiment. In order to compare and contrast both methods, we examined the syntactic phenomenon usually referred to as the Adjacency Condition (AC) (apud Stowell, 1981), which imposes a condition of adjacency between verb and object. Our interest in the AC comes from the fact that it is a subtle feature of English grammar which is absent in Spanish, and this provides an excellent springboard to create minimal code-switched pairs that allow us to formulate a clear research question that can be tested using both methods.
Address
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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 NEUROBIT; no menciona Approved no
Call Number Admin @ si @ SLP2018 Serial 2994
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Author Andrew Nolan; Daniel Serrano; Aura Hernandez-Sabate; Daniel Ponsa; Antonio Lopez
Title Obstacle mapping module for quadrotors on outdoor Search and Rescue operations Type Conference Article
Year 2013 Publication International Micro Air Vehicle Conference and Flight Competition Abbreviated Journal
Volume Issue Pages
Keywords (up) UAV
Abstract Obstacle avoidance remains a challenging task for Micro Aerial Vehicles (MAV), due to their limited payload capacity to carry advanced sensors. Unlike larger vehicles, MAV can only carry light weight sensors, for instance a camera, which is our main assumption in this work. We explore passive monocular depth estimation and propose a novel method Position Aided Depth Estimation
(PADE). We analyse PADE performance and compare it against the extensively used Time To Collision (TTC). We evaluate the accuracy, robustness to noise and speed of three Optical Flow (OF) techniques, combined with both depth estimation methods. Our results show PADE is more accurate than TTC at depths between 0-12 meters and is less sensitive to noise. Our findings highlight the potential application of PADE for MAV to perform safe autonomous navigation in
unknown and unstructured environments.
Address Toulouse; France; September 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 ISBN Medium
Area Expedition Conference IMAV
Notes ADAS; 600.054; 600.057;IAM Approved no
Call Number Admin @ si @ NSH2013 Serial 2371
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Author Kaida Xiao; Sophie Wuerger; Chenyang Fu; Dimosthenis Karatzas
Title Unique Hue Data for Colour Appearance Models. Part i: Loci of Unique Hues and Hue Uniformity Type Journal Article
Year 2011 Publication Color Research & Application Abbreviated Journal CRA
Volume 36 Issue 5 Pages 316-323
Keywords (up) unique hues; colour appearance models; CIECAM02; hue uniformity
Abstract Psychophysical experiments were conducted to assess unique hues on a CRT display for a large sample of colour-normal observers (n 1⁄4 185). These data were then used to evaluate the most commonly used colour appear- ance model, CIECAM02, by transforming the CIEXYZ tris- timulus values of the unique hues to the CIECAM02 colour appearance attributes, lightness, chroma and hue angle. We report two findings: (1) the hue angles derived from our unique hue data are inconsistent with the commonly used Natural Color System hues that are incorporated in the CIECAM02 model. We argue that our predicted unique hue angles (derived from our large dataset) provide a more reliable standard for colour management applications when the precise specification of these salient colours is im- portant. (2) We test hue uniformity for CIECAM02 in all four unique hues and show significant disagreements for all hues, except for unique red which seems to be invariant under lightness changes. Our dataset is useful to improve the CIECAM02 model as it provides reliable data for benchmarking.
Address
Corporate Author Thesis
Publisher Wiley Periodicals Inc 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 @ XWF2011 Serial 1816
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Author Cesar de Souza; Adrien Gaidon; Eleonora Vig; Antonio Lopez
Title System and method for video classification using a hybrid unsupervised and supervised multi-layer architecture Type Patent
Year 2018 Publication US9946933B2 Abbreviated Journal
Volume Issue Pages
Keywords (up) US9946933B2
Abstract A computer-implemented video classification method and system are disclosed. The method includes receiving an input video including a sequence of frames. At least one transformation of the input video is generated, each transformation including a sequence of frames. For the input video and each transformation, local descriptors are extracted from the respective sequence of frames. The local descriptors of the input video and each transformation are aggregated to form an aggregated feature vector with a first set of processing layers learned using unsupervised learning. An output classification value is generated for the input video, based on the aggregated feature vector with a second set of processing layers learned using supervised learning.
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 ADAS; 600.118 Approved no
Call Number Admin @ si @ SGV2018 Serial 3255
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Author Aura Hernandez-Sabate; Debora Gil; Albert Teis
Title How Do Conservation Laws Define a Motion Suppression Score in In-Vivo Ivus Sequences? Type Conference Article
Year 2007 Publication Proc. IEEE Ultrasonics Symp Abbreviated Journal
Volume Issue Pages 2231-2234
Keywords (up) validation standards; IVUS motion compensation; conservation laws.
Abstract Evaluation of arterial tissue biomechanics for diagnosis and treatment of cardiovascular diseases is an active research field in the biomedical imaging processing area. IntraVascular UltraSound (IVUS) is a unique tool for such assessment since it reflects tissue morphology and deformation. A proper quantification and visualization of both properties is hindered by vessel structures misalignments introduced by cardiac dynamics. This has encouraged development of IVUS motion compensation techniques. However, there is a lack of an objective evaluation of motion reduction ensuring a reliable clinical application This work reports a novel score, the Conservation of Density Rate (CDR), for validation of motion compensation in in-vivo pullbacks. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; while results in in vivo pullbacks show its reliability in clinical cases.
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 IAM Approved no
Call Number IAM @ iam @ HTG2007 Serial 1550
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Author Debora Gil; Oriol Rodriguez-Leor; Petia Radeva; Aura Hernandez-Sabate
Title Assessing Artery Motion Compensation in IVUS Type Book Chapter
Year 2007 Publication Computer Analysis Of Images And Patterns Abbreviated Journal LNCS
Volume 4673 Issue Pages 213-220
Keywords (up) validation standards; quality measures; IVUS motion compensation; conservation laws; Fourier development
Abstract Cardiac dynamics suppression is a main issue for visual improvement and computation of tissue mechanical properties in IntraVascular UltraSound (IVUS). Although in recent times several motion compensation techniques have arisen, there is a lack of objective evaluation of motion reduction in in vivo pullbacks. We consider that the assessment protocol deserves special attention for the sake of a clinical applicability as reliable as possible. Our work focuses on defining a quality measure and a validation protocol assessing IVUS motion compensation. On the grounds of continuum mechanics laws we introduce a novel score measuring motion reduction in in vivo sequences. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; while results in in vivo pullbacks show its reliability in clinical cases.
Address
Corporate Author Thesis
Publisher Springerlink Place of Publication Heidelberg Editor
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-3-540-74271-5 Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GRR2007 Serial 1540
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Author Aura Hernandez-Sabate; Debora Gil; David Roche; Monica M. S. Matsumoto; Sergio S. Furuie
Title Inferring the Performance of Medical Imaging Algorithms Type Conference Article
Year 2011 Publication 14th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal
Volume 6854 Issue Pages 520-528
Keywords (up) Validation, Statistical Inference, Medical Imaging Algorithms.
Abstract Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence.
Address Sevilla
Corporate Author Thesis
Publisher Springer-Verlag Berlin Heidelberg Place of Publication Berlin Editor Pedro Real; Daniel Diaz-Pernil; Helena Molina-Abril; Ainhoa Berciano; Walter Kropatsch
Language Summary Language Original Title
Series Editor Series Title L Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CAIP
Notes IAM; ADAS Approved no
Call Number IAM @ iam @ HGR2011 Serial 1676
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Author Mohamed Ilyes Lakhal; Hakan Cevikalp; Sergio Escalera
Title CRN: End-to-end Convolutional Recurrent Network Structure Applied to Vehicle Classification Type Conference Article
Year 2018 Publication 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications Abbreviated Journal
Volume 5 Issue Pages 137-144
Keywords (up) Vehicle Classification; Deep Learning; End-to-end Learning
Abstract Vehicle type classification is considered to be a central part of Intelligent Traffic Systems. In the recent years, deep learning methods have emerged in as being the state-of-the-art in many computer vision tasks. In this paper, we present a novel yet simple deep learning framework for the vehicle type classification problem. We propose an end-to-end trainable system, that combines convolution neural network for feature extraction and recurrent neural network as a classifier. The recurrent network structure is used to handle various types of feature inputs, and at the same time allows to produce a single or a set of class predictions. In order to assess the effectiveness of our solution, we have conducted a set of experiments in two public datasets, obtaining state of the art results. In addition, we also report results on the newly released MIO-TCD dataset.
Address Funchal; Madeira; Portugal; January 2018
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 VISAPP
Notes HUPBA Approved no
Call Number Admin @ si @ LCE2018a Serial 3094
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Author Daniel Ponsa; Antonio Lopez; Joan Serrat; Felipe Lumbreras; T. Graf
Title Multiple Vehicle 3D Tracking Using an Unscented Kalman Filter Type Miscellaneous
Year 2005 Publication Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, 1108–1113, ISBN:0–7803–9216–7 Abbreviated Journal
Volume Issue Pages
Keywords (up) vehicle detection
Abstract
Address Vienna (Austria)
Corporate Author Thesis
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Notes ADAS Approved no
Call Number ADAS @ adas @ PLS2005 Serial 615
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Author Daniel Ponsa; Antonio Lopez
Title Vehicle Trajectory Estimation based on Monocular Vision Type Conference Article
Year 2007 Publication 3rd Iberian Conference on Pattern Recognition and Image Analysis, LNCS 4477 Abbreviated Journal
Volume Issue Pages 587-594
Keywords (up) vehicle detection
Abstract
Address Girona (Spain)
Corporate Author Thesis
Publisher Place of Publication Editor
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Notes ADAS Approved no
Call Number ADAS @ adas @ PoL2007a Serial 785
Permanent link to this record
 
 
Author Daniel Ponsa; Antonio Lopez
Title Cascade of Classifiers for Vehicle Detection Type Conference Article
Year 2007 Publication Advanced Concepts for Intelligent Vision Systems, LNCS 4678, volume 1, pp. 980–989 Abbreviated Journal
Volume Issue Pages
Keywords (up) vehicle detection
Abstract
Address Delft (Netherlands)
Corporate Author Thesis
Publisher Place of Publication Editor
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Series Editor Series Title Abbreviated Series Title
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Notes ADAS Approved no
Call Number ADAS @ adas @ PoL2007c Serial 935
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Author Daniel Ponsa; Joan Serrat; Antonio Lopez
Title On-board image-based vehicle detection and tracking Type Journal Article
Year 2011 Publication Transactions of the Institute of Measurement and Control Abbreviated Journal TIM
Volume 33 Issue 7 Pages 783-805
Keywords (up) vehicle detection
Abstract In this paper we present a computer vision system for daytime vehicle detection and localization, an essential step in the development of several types of advanced driver assistance systems. It has a reduced processing time and high accuracy thanks to the combination of vehicle detection with lane-markings estimation and temporal tracking of both vehicles and lane markings. Concerning vehicle detection, our main contribution is a frame scanning process that inspects images according to the geometry of image formation, and with an Adaboost-based detector that is robust to the variability in the different vehicle types (car, van, truck) and lighting conditions. In addition, we propose a new method to estimate the most likely three-dimensional locations of vehicles on the road ahead. With regards to the lane-markings estimation component, we have two main contributions. First, we employ a different image feature to the other commonly used edges: we use ridges, which are better suited to this problem. Second, we adapt RANSAC, a generic robust estimation method, to fit a parametric model of a pair of lane markings to the image features. We qualitatively assess our vehicle detection system in sequences captured on several road types and under very different lighting conditions. The processed videos are available on a web page associated with this paper. A quantitative evaluation of the system has shown quite accurate results (a low number of false positives and negatives) at a reasonable computation time.
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Notes ADAS Approved no
Call Number ADAS @ adas @ PSL2011 Serial 1413
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Author Victor Ponce; Sergio Escalera; Marc Perez; Oriol Janes; Xavier Baro
Title Non-Verbal Communication Analysis in Victim-Offender Mediations Type Journal Article
Year 2015 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 67 Issue 1 Pages 19-27
Keywords (up) Victim–Offender Mediation; Multi-modal human behavior analysis; Face and gesture recognition; Social signal processing; Computer vision; Machine learning
Abstract We present a non-invasive ambient intelligence framework for the semi-automatic analysis of non-verbal communication applied to the restorative justice field. We propose the use of computer vision and social signal processing technologies in real scenarios of Victim–Offender Mediations, applying feature extraction techniques to multi-modal audio-RGB-depth data. We compute a set of behavioral indicators that define communicative cues from the fields of psychology and observational methodology. We test our methodology on data captured in real Victim–Offender Mediation sessions in Catalonia. We define the ground truth based on expert opinions when annotating the observed social responses. Using different state of the art binary classification approaches, our system achieves recognition accuracies of 86% when predicting satisfaction, and 79% when predicting both agreement and receptivity. Applying a regression strategy, we obtain a mean deviation for the predictions between 0.5 and 0.7 in the range [1–5] for the computed social signals.
Address
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Publisher Place of Publication Editor
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Notes HuPBA;MV Approved no
Call Number Admin @ si @ PEP2015 Serial 2583
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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 13-28
Keywords (up) 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
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Series Editor Series Title Abbreviated Series Title
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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 Joan Serrat; Ferran Diego; Felipe Lumbreras; Jose Manuel Alvarez; Antonio Lopez; C. Elvira
Title Dynamic Comparison of Headlights Type Journal Article
Year 2008 Publication Journal of Automobile Engineering Abbreviated Journal
Volume 222 Issue 5 Pages 643–656
Keywords (up) video alignment
Abstract
Address
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Publisher Place of Publication Editor
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Notes ADAS Approved no
Call Number ADAS @ adas @ SDL2008a Serial 958
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