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Author David Geronimo; Antonio Lopez
Title Deteccion de Peatones para Sistemas Avanzados de Asistencia al Conductor Type Miscellaneous
Year 2010 Publication UAB Divulga Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Los sistemas de asistencia al conductor, y particularmente los sistemas de protección de peatones, representan uno de los campos de investigación más activos dedicados a la mejora de la seguridad vial. El mayor desafío es el desarrollo de sistemas a bordo fiables de detección de peatones. En esta revisión del estado de la técnica de la detección de peatones, se divide el problema en diferentes etapas, cada una con responsabilidades propias dentro del sistema. Esta división facilita el posterior análisis y discusión de cada uno de los métodos en la literatura, favoreciendo la comparación entre ellos. Finalmente se discuten los temas más importantes de este campo poniendo especial énfasis en las necesidades actuales y los desafíos futuros.
Address Bellaterra (Catalonia), Spain
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 (down) spreading;ADAS Approved no
Call Number ADAS @ adas @ GeL2010a Serial 1414
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Author David Geronimo; Antonio Lopez
Title Sistema de deteccion de peatones Type Miscellaneous
Year 2010 Publication UAB Divulga Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Durante la próxima década, los sistemas de protección de peatones jugarán un papel fundamental en el reto de mejorar la seguridad viaria. El objetivo principal de estos sistemas, detectar peatones en entornos urbanos, implica procesar imágenes de escenas exteriores desde una plataforma móvil para buscar objetos de aspecto variable como son las personas. Dadas estas dificultades, estos sistemas hacen uso de las últimas técnicas de visión por computador. Esta propuesta consiste en un sistema de tres módulos basado tanto en información 2D como en 3D. El primer módulo utiliza información 3D para hacer una estimación de los parámetros de la carretera y seleccionar regiones de interés que serán analizadas después. El segundo módulo utiliza un clasificador de ventanas 2D para etiquetar las mencionadas regiones como peatón o no peatón. El módulo final vuelve a utilizar de nuevo la información 3D para verificar las regiones clasificadas y, con información 2D, refinar los resultados finales. Los resultados experimentales son positivos tanto en rendimiento como en tiempo de cómputo.
Address Bellaterra (Spain)
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 (down) spreading;ADAS Approved no
Call Number ADAS @ adas @ GeL2010b Serial 1473
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Author Bogdan Raducanu; Jordi Vitria; Ales Leonardis
Title Online pattern recognition and machine learning techniques for computer-vision: Theory and applications Type Journal Article
Year 2010 Publication Image and Vision Computing Abbreviated Journal IMAVIS
Volume 28 Issue 7 Pages 1063–1064
Keywords
Abstract (Editorial for the Special Issue on Online pattern recognition and machine learning techniques)
In real life, visual learning is supposed to be a continuous process. This paradigm has found its way also in artificial vision systems. There is an increasing trend in pattern recognition represented by online learning approaches, which aims at continuously updating the data representation when new information arrives. Starting with a minimal dataset, the initial knowledge is expanded by incorporating incoming instances, which may have not been previously available or foreseen at the system’s design stage. An interesting characteristic of this strategy is that the train and test phases take place simultaneously. Given the increasing interest in this subject, the aim of this special issue is to be a landmark event in the development of online learning techniques and their applications with the hope that it will capture the interest of a wider audience and will attract even more researchers. We received 19 contributions, of which 9 have been accepted for publication, after having been subjected to usual peer review process.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0262-8856 ISBN Medium
Area Expedition Conference
Notes (down) OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ RVL2010 Serial 1280
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Author Mario Rojas; David Masip; A. Todorov; Jordi Vitria
Title Automatic Point-based Facial Trait Judgments Evaluation Type Conference Article
Year 2010 Publication 23rd IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages 2715–2720
Keywords
Abstract Humans constantly evaluate the personalities of other people using their faces. Facial trait judgments have been studied in the psychological field, and have been determined to influence important social outcomes of our lives, such as elections outcomes and social relationships. Recent work on textual descriptions of faces has shown that trait judgments are highly correlated. Further, behavioral studies suggest that two orthogonal dimensions, valence and dominance, can describe the basis of the human judgments from faces. In this paper, we used a corpus of behavioral data of judgments on different trait dimensions to automatically learn a trait predictor from facial pixel images. We study whether trait evaluations performed by humans can be learned using machine learning classifiers, and used later in automatic evaluations of new facial images. The experiments performed using local point-based descriptors show promising results in the evaluation of the main traits.
Address San Francisco CA, USA
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 1063-6919 ISBN 978-1-4244-6984-0 Medium
Area Expedition Conference CVPR
Notes (down) OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ RMT2010 Serial 1282
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Author Fadi Dornaika; Bogdan Raducanu
Title Single Snapshot 3D Head Pose Initialization for Tracking in Human Robot Interaction Scenario Type Conference Article
Year 2010 Publication 1st International Workshop on Computer Vision for Human-Robot Interaction Abbreviated Journal
Volume Issue Pages 32–39
Keywords 1st International Workshop on Computer Vision for Human-Robot Interaction, in conjunction with IEEE CVPR 2010
Abstract This paper presents an automatic 3D head pose initialization scheme for a real-time face tracker with application to human-robot interaction. It has two main contributions. First, we propose an automatic 3D head pose and person specific face shape estimation, based on a 3D deformable model. The proposed approach serves to initialize our realtime 3D face tracker. What makes this contribution very attractive is that the initialization step can cope with faces
under arbitrary pose, so it is not limited only to near-frontal views. Second, the previous framework is used to develop an application in which the orientation of an AIBO’s camera can be controlled through the imitation of user’s head pose.
In our scenario, this application is used to build panoramic images from overlapping snapshots. Experiments on real videos confirm the robustness and usefulness of the proposed methods.
Address San Francisco; CA; USA; June 2010
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 2160-7508 ISBN 978-1-4244-7029-7 Medium
Area Expedition Conference CVPRW
Notes (down) OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ DoR2010a Serial 1309
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Author Fadi Dornaika; Bogdan Raducanu
Title Person-specific face shape estimation under varying head pose from single snapshots Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 3496–3499
Keywords
Abstract This paper presents a new method for person-specific face shape estimation under varying head pose of a previously unseen person from a single image. We describe a featureless approach based on a deformable 3D model and a learned face subspace. The proposed approach is based on maximizing a likelihood measure associated with a learned face subspace, which is carried out by a stochastic and genetic optimizer. We conducted the experiments on a subset of Honda Video Database showing the feasibility and robustness of the proposed approach. For this reason, our approach could lend itself nicely to complex frameworks involving 3D face tracking and face gesture recognition in monocular videos.
Address Istanbul, Turkey
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 1051-4651 ISBN 978-1-4244-7542-1 Medium
Area Expedition Conference ICPR
Notes (down) OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ DoR2010b Serial 1361
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Author Cesar Isaza; Joaquin Salas; Bogdan Raducanu
Title Toward the Detection of Urban Infrastructures Edge Shadows Type Conference Article
Year 2010 Publication 12th International Conference on Advanced Concepts for Intelligent Vision Systems Abbreviated Journal
Volume 6474 Issue I Pages 30–37
Keywords
Abstract In this paper, we propose a novel technique to detect the shadows cast by urban infrastructure, such as buildings, billboards, and traffic signs, using a sequence of images taken from a fixed camera. In our approach, we compute two different background models in parallel: one for the edges and one for the reflected light intensity. An algorithm is proposed to train the system to distinguish between moving edges in general and edges that belong to static objects, creating an edge background model. Then, during operation, a background intensity model allow us to separate between moving and static objects. Those edges included in the moving objects and those that belong to the edge background model are subtracted from the current image edges. The remaining edges are the ones cast by urban infrastructure. Our method is tested on a typical crossroad scene and the results show that the approach is sound and promising.
Address Sydney, Australia
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor eds. Blanc–Talon et al
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-17687-6 Medium
Area Expedition Conference ACIVS
Notes (down) OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ ISR2010 Serial 1458
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Author Joan Arnedo-Moreno; Agata Lapedriza
Title Visualizing key authenticity: turning your face into your public key Type Conference Article
Year 2010 Publication 6th China International Conference on Information Security and Cryptology Abbreviated Journal
Volume Issue Pages 605-618
Keywords
Abstract Biometric information has become a technology complementary to cryptography, allowing to conveniently manage cryptographic data. Two important needs are ful lled: rst of all, making such data always readily available, and additionally, making its legitimate owner easily identi able. In this work we propose a signature system which integrates face recognition biometrics with and identity-based signature scheme, so the user's face e ectively becomes his public key and system ID. Thus, other users may verify messages using photos of the claimed sender, providing a reasonable trade-o between system security and usability, as well as a much more straightforward public key authenticity and distribution process.
Address
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 Inscrypt
Notes (down) OR;MV Approved no
Call Number Admin @ si @ ArL2010c Serial 2149
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Author Michal Drozdzal; Laura Igual; Petia Radeva; Jordi Vitria; Carolina Malagelada; Fernando Azpiroz
Title Aligning Endoluminal Scene Sequences in Wireless Capsule Endoscopy Type Conference Article
Year 2010 Publication IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis Abbreviated Journal
Volume Issue Pages 117–124
Keywords
Abstract Intestinal motility analysis is an important examination in detection of various intestinal malfunctions. One of the big challenges of automatic motility analysis is how to compare sequence of images and extract dynamic paterns taking into account the high deformability of the intestine wall as well as the capsule motion. From clinical point of view the ability to align endoluminal scene sequences will help to find regions of similar intestinal activity and in this way will provide a valuable information on intestinal motility problems. This work, for first time, addresses the problem of aligning endoluminal sequences taking into account motion and structure of the intestine. To describe motility in the sequence, we propose different descriptors based on the Sift Flow algorithm, namely: (1) Histograms of Sift Flow Directions to describe the flow course, (2) Sift Descriptors to represent image intestine structure and (3) Sift Flow Magnitude to quantify intestine deformation. We show that the merge of all three descriptors provides robust information on sequence description in terms of motility. Moreover, we develop a novel methodology to rank the intestinal sequences based on the expert feedback about relevance of the results. The experimental results show that the selected descriptors are useful in the alignment and similarity description and the proposed method allows the analysis of the WCE.
Address San Francisco; CA; USA; June 2010
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 2160-7508 ISBN 978-1-4244-7029-7 Medium
Area Expedition Conference MMBIA
Notes (down) OR;MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ DIR2010 Serial 1316
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Author Michal Drozdzal; Laura Igual; Jordi Vitria; Petia Radeva; Carolina Malagelada; Fernando Azpiroz
Title SIFT flow-based Sequences Alignment Type Conference Article
Year 2010 Publication Medical Image Computing in Catalunya: Graduate Student Workshop Abbreviated Journal
Volume Issue Pages 7–8
Keywords
Abstract
Address Girona, Spain
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 MICCAT
Notes (down) OR;MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ DIV2010 Serial 1475
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Author Santiago Segui; Michal Drozdzal; Petia Radeva; Jordi Vitria
Title Severe Motility Diagnosis using WCE Type Conference Article
Year 2010 Publication Medical Image Computing in Catalunya: Graduate Student Workshop Abbreviated Journal
Volume Issue Pages 45–46
Keywords
Abstract
Address Girona, Spain
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 MICCAT
Notes (down) OR;MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ SDR2010 Serial 1478
Permanent link to this record
 
 
Author Sergio Escalera; Oriol Pujol; Petia Radeva; Jordi Vitria; Maria Teresa Anguera
Title Automatic Detection of Dominance and Expected Interest Type Journal Article
Year 2010 Publication EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ
Volume Issue Pages 12
Keywords
Abstract Article ID 491819
Social Signal Processing is an emergent area of research that focuses on the analysis of social constructs. Dominance and interest are two of these social constructs. Dominance refers to the level of influence a person has in a conversation. Interest, when referred in terms of group interactions, can be defined as the degree of engagement that the members of a group collectively display during their interaction. In this paper, we argue that only using behavioral motion information, we are able to predict the interest of observers when looking at face-to-face interactions as well as the dominant people. First, we propose a simple set of movement-based features from body, face, and mouth activity in order to define a higher set of interaction indicators. The considered indicators are manually annotated by observers. Based on the opinions obtained, we define an automatic binary dominance detection problem and a multiclass interest quantification problem. Error-Correcting Output Codes framework is used to learn to rank the perceived observer's interest in face-to-face interactions meanwhile Adaboost is used to solve the dominant detection problem. The automatic system shows good correlation between the automatic categorization results and the manual ranking made by the observers in both dominance and interest detection problems.
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 1110-8657 ISBN Medium
Area Expedition Conference
Notes (down) OR;MILAB;HUPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ EPR2010d Serial 1283
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Author Miguel Angel Bautista; Xavier Baro; Oriol Pujol; Petia Radeva; Jordi Vitria; Sergio Escalera
Title Compact Evolutive Design of Error-Correcting Output Codes Type Conference Article
Year 2010 Publication Supervised and Unsupervised Ensemble Methods and their Applications in the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases Abbreviated Journal
Volume Issue Pages 119-128
Keywords Ensemble of Dichotomizers; Error-Correcting Output Codes; Evolutionary optimization
Abstract The classi cation of large number of object categories is a challenging trend in the Machine Learning eld. In literature, this is often addressed using an ensemble of classi ers. In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for the combination of classi ers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classi ers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a minimal design of ECOC in terms of the number of classi ers. Evolutionary computation is used for tuning the parameters of the classi ers and looking for the best Minimal ECOC code con guration. The results over several public UCI data sets and a challenging multi-class Computer Vision problem show that the proposed methodology obtains comparable and even better results than state-of-the-art ECOC methodologies with far less number of dichotomizers.
Address Barcelona (Spain)
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 SUEMA
Notes (down) OR;MILAB;HUPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ BBP2010 Serial 1363
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Author Sergio Escalera; Petia Radeva; Jordi Vitria; Xavier Baro; Bogdan Raducanu
Title Modelling and Analyzing Multimodal Dyadic Interactions Using Social Networks Type Conference Article
Year 2010 Publication 12th International Conference on Multimodal Interfaces and 7th Workshop on Machine Learning for Multimodal Interaction. Abbreviated Journal
Volume Issue Pages
Keywords Social interaction; Multimodal fusion, Influence model; Social network analysis
Abstract Social network analysis became a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from
multimodal dyadic interactions. First, speech detection is performed through an audio/visual fusion scheme based on stacked sequential learning. In the audio domain, speech is detected through clusterization of audio features. Clusters
are modelled by means of an One-state Hidden Markov Model containing a diagonal covariance Gaussian Mixture Model. In the visual domain, speech detection is performed through differential-based feature extraction from the segmented
mouth region, and a dynamic programming matching procedure. Second, in order to model the dyadic interactions, we employed the Influence Model whose states
encode the previous integrated audio/visual data. Third, the social network is extracted based on the estimated influences. For our study, we used a set of videos belonging to New York Times’ Blogging Heads opinion blog. The results
are reported both in terms of accuracy of the audio/visual data fusion and centrality measures used to characterize the social network.
Address Beijing (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 ICMI-MLI
Notes (down) OR;MILAB;HUPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ ERV2010 Serial 1427
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Author Sergio Escalera; Oriol Pujol; Eric Laciar; Jordi Vitria; Esther Pueyo; Petia Radeva
Title Classification of Coronary Damage in Chronic Chagasic Patients Type Book Chapter
Year 2010 Publication Intelligent Systems – From Theory to Practice. Studies in Computational Intelligence Abbreviated Journal
Volume 299 Issue Pages 461-478
Keywords Chagas disease; Error-Correcting Output Codes; High resolution ECG; Decoding
Abstract Post Conference IEEE-IS 2008
The Chagas’ disease is endemic in all Latin America, affecting millions of people in the continent. In order to diagnose and treat the chagas’ disease, it is important to detect and measure the coronary damage of the patient. In this paper,
we analyze and categorize patients into different groups based on the coronary damage produced by the disease. Based on the features of the heart cycle extracted using high resolution ECG, a multi-class scheme of Error-Correcting Output Codes (ECOC)is formulated and successfully applied. The results show that the proposed scheme obtains significant performance improvements compared to previous works and state-of-the-art ECOC designs.
Address
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Editor V. Sgurev, M. Hadjiski (eds)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes (down) OR;MILAB;HUPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ EPL2010 Serial 1452
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