Records |
Author |
Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva |
Title |
Adaptable image cuts for motility inspection using WCE |
Type |
Journal Article |
Year |
2013 |
Publication |
Computerized Medical Imaging and Graphics |
Abbreviated Journal |
CMIG |
Volume |
37 |
Issue ![sorted by Issue field, ascending order (up)](img/sort_asc.gif) |
1 |
Pages |
72-80 |
Keywords |
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Abstract |
The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE. |
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MILAB; OR; 600.046; 605.203 |
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no |
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Admin @ si @ DSM2012 |
Serial |
2151 |
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Author |
Fadi Dornaika; Abdelmalik Moujahid; Bogdan Raducanu |
Title |
Facial expression recognition using tracked facial actions: Classifier performance analysis |
Type |
Journal Article |
Year |
2013 |
Publication |
Engineering Applications of Artificial Intelligence |
Abbreviated Journal |
EAAI |
Volume |
26 |
Issue ![sorted by Issue field, ascending order (up)](img/sort_asc.gif) |
1 |
Pages |
467-477 |
Keywords |
Visual face tracking; 3D deformable models; Facial actions; Dynamic facial expression recognition; Human–computer interaction |
Abstract |
In this paper, we address the analysis and recognition of facial expressions in continuous videos. More precisely, we study classifiers performance that exploit head pose independent temporal facial action parameters. These are provided by an appearance-based 3D face tracker that simultaneously provides the 3D head pose and facial actions. The use of such tracker makes the recognition pose- and texture-independent. Two different schemes are studied. The first scheme adopts a dynamic time warping technique for recognizing expressions where training data are given by temporal signatures associated with different universal facial expressions. The second scheme models temporal signatures associated with facial actions with fixed length feature vectors (observations), and uses some machine learning algorithms in order to recognize the displayed expression. Experiments quantified the performance of different schemes. These were carried out on CMU video sequences and home-made video sequences. The results show that the use of dimension reduction techniques on the extracted time series can improve the classification performance. Moreover, these experiments show that the best recognition rate can be above 90%. |
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Elsevier |
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OR; 600.046;MV |
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no |
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Admin @ si @ DMR2013 |
Serial |
2185 |
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Author |
Rozenn Dhayot; Fernando Vilariño; Gerard Lacey |
Title |
Improving the Quality of Color Colonoscopy Videos |
Type |
Journal Article |
Year |
2008 |
Publication |
EURASIP Journal on Image and Video Processing |
Abbreviated Journal |
EURASIP JIVP |
Volume |
139429 |
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1 |
Pages |
1-9 |
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800 |
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Notes |
MV;SIAI |
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no |
Call Number |
fernando @ fernando @ |
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2422 |
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Author |
Shida Beigpour; Christian Riess; Joost Van de Weijer; Elli Angelopoulou |
Title |
Multi-Illuminant Estimation with Conditional Random Fields |
Type |
Journal Article |
Year |
2014 |
Publication |
IEEE Transactions on Image Processing |
Abbreviated Journal |
TIP |
Volume |
23 |
Issue ![sorted by Issue field, ascending order (up)](img/sort_asc.gif) |
1 |
Pages |
83-95 |
Keywords |
color constancy; CRF; multi-illuminant |
Abstract |
Most existing color constancy algorithms assume uniform illumination. However, in real-world scenes, this is not often the case. Thus, we propose a novel framework for estimating the colors of multiple illuminants and their spatial distribution in the scene. We formulate this problem as an energy minimization task within a conditional random field over a set of local illuminant estimates. In order to quantitatively evaluate the proposed method, we created a novel data set of two-dominant-illuminant images comprised of laboratory, indoor, and outdoor scenes. Unlike prior work, our database includes accurate pixel-wise ground truth illuminant information. The performance of our method is evaluated on multiple data sets. Experimental results show that our framework clearly outperforms single illuminant estimators as well as a recently proposed multi-illuminant estimation approach. |
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ISSN |
1057-7149 |
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Notes |
CIC; LAMP; 600.074; 600.079 |
Approved |
no |
Call Number |
Admin @ si @ BRW2014 |
Serial |
2451 |
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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 ![sorted by Issue field, ascending order (up)](img/sort_asc.gif) |
1 |
Pages |
19-27 |
Keywords |
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. |
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Notes |
HuPBA;MV |
Approved |
no |
Call Number |
Admin @ si @ PEP2015 |
Serial |
2583 |
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Author |
Victor Ponce; Mario Gorga; Xavier Baro; Petia Radeva; Sergio Escalera |
Title |
Análisis de la expresión oral y gestual en proyectos fin de carrera vía un sistema de visión artificial |
Type |
Journal Article |
Year |
2011 |
Publication |
ReVisión |
Abbreviated Journal |
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Volume |
4 |
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1 |
Pages |
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Abstract |
La comunicación y expresión oral es una competencia de especial relevancia en el EEES. No obstante, en muchas enseñanzas superiores la puesta en práctica de esta competencia ha sido relegada principalmente a la presentación de proyectos fin de carrera. Dentro de un proyecto de innovación docente, se ha desarrollado una herramienta informática para la extracción de información objetiva para el análisis de la expresión oral y gestual de los alumnos. El objetivo es dar un “feedback” a los estudiantes que les permita mejorar la calidad de sus presentaciones. El prototipo inicial que se presenta en este trabajo permite extraer de forma automática información audiovisual y analizarla mediante técnicas de aprendizaje. El sistema ha sido aplicado a 15 proyectos fin de carrera y 15 exposiciones dentro de una asignatura de cuarto curso. Los resultados obtenidos muestran la viabilidad del sistema para sugerir factores que ayuden tanto en el éxito de la comunicación así como en los criterios de evaluación. |
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1989-1199 |
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Notes |
HuPBA; MILAB;MV |
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no |
Call Number |
Admin @ si @ PGB2011d |
Serial |
2514 |
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Author |
Mohammad Rouhani; Angel Sappa; E. Boyer |
Title |
Implicit B-Spline Surface Reconstruction |
Type |
Journal Article |
Year |
2015 |
Publication |
IEEE Transactions on Image Processing |
Abbreviated Journal |
TIP |
Volume |
24 |
Issue ![sorted by Issue field, ascending order (up)](img/sort_asc.gif) |
1 |
Pages |
22 - 32 |
Keywords |
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Abstract |
This paper presents a fast and flexible curve, and surface reconstruction technique based on implicit B-spline. This representation does not require any parameterization and it is locally supported. This fact has been exploited in this paper to propose a reconstruction technique through solving a sparse system of equations. This method is further accelerated to reduce the dimension to the active control lattice. Moreover, the surface smoothness and user interaction are allowed for controlling the surface. Finally, a novel weighting technique has been introduced in order to blend small patches and smooth them in the overlapping regions. The whole framework is very fast and efficient and can handle large cloud of points with very low computational cost. The experimental results show the flexibility and accuracy of the proposed algorithm to describe objects with complex topologies. Comparisons with other fitting methods highlight the superiority of the proposed approach in the presence of noise and missing data. |
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ISSN |
1057-7149 |
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Notes |
ADAS; 600.076 |
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no |
Call Number |
Admin @ si @ RSB2015 |
Serial |
2541 |
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Author |
Alvaro Cepero; Albert Clapes; Sergio Escalera |
Title |
Automatic non-verbal communication skills analysis: a quantitative evaluation |
Type |
Journal Article |
Year |
2015 |
Publication |
AI Communications |
Abbreviated Journal |
AIC |
Volume |
28 |
Issue ![sorted by Issue field, ascending order (up)](img/sort_asc.gif) |
1 |
Pages |
87-101 |
Keywords |
Social signal processing; human behavior analysis; multi-modal data description; multi-modal data fusion; non-verbal communication analysis; e-Learning |
Abstract |
The oral communication competence is defined on the top of the most relevant skills for one's professional and personal life. Because of the importance of communication in our activities of daily living, it is crucial to study methods to evaluate and provide the necessary feedback that can be used in order to improve these communication capabilities and, therefore, learn how to express ourselves better. In this work, we propose a system capable of evaluating quantitatively the quality of oral presentations in an automatic fashion. The system is based on a multi-modal RGB, depth, and audio data description and a fusion approach in order to recognize behavioral cues and train classifiers able to eventually predict communication quality levels. The performance of the proposed system is tested on a novel dataset containing Bachelor thesis' real defenses, presentations from an 8th semester Bachelor courses, and Master courses' presentations at Universitat de Barcelona. Using as groundtruth the marks assigned by actual instructors, our system achieves high performance categorizing and ranking presentations by their quality, and also making real-valued mark predictions. |
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0921-7126 |
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HUPBA;MILAB |
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no |
Call Number |
Admin @ si @ CCE2015 |
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2549 |
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Author |
G. Zahnd; Simone Balocco; A. Serusclat; P. Moulin; M. Orkisz; D. Vray |
Title |
Progressive attenuation of the longitudinal kinetics in the common carotid artery: preliminary in vivo assessment Ultrasound in Medicine and Biology |
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Journal Article |
Year |
2015 |
Publication |
Ultrasound in Medicine and Biology |
Abbreviated Journal |
UMB |
Volume |
41 |
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1 |
Pages |
339-345 |
Keywords |
Arterial stiffness; Atherosclerosis; Common carotid artery; Longitudinal kinetics; Motion tracking; Ultrasound imaging |
Abstract |
Longitudinal kinetics (LOKI) of the arterial wall consists of the shearing motion of the intima-media complex over the adventitia layer in the direction parallel to the blood flow during the cardiac cycle. The aim of this study was to investigate the local variability of LOKI amplitude along the length of the vessel. By use of a previously validated motion-estimation framework, 35 in vivo longitudinal B-mode ultrasound cine loops of healthy common carotid arteries were analyzed. Results indicated that LOKI amplitude is progressively attenuated along the length of the artery, as it is larger in regions located on the proximal side of the image (i.e., toward the heart) and smaller in regions located on the distal side of the image (i.e., toward the head), with an average attenuation coefficient of -2.5 ± 2.0%/mm. Reported for the first time in this study, this phenomenon is likely to be of great importance in improving understanding of atherosclerosis mechanisms, and has the potential to be a novel index of arterial stiffness. |
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MILAB |
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no |
Call Number |
Admin @ si @ ZBS2014 |
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2556 |
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Author |
Lluis Pere de las Heras; Oriol Ramos Terrades; Sergi Robles; Gemma Sanchez |
Title |
CVC-FP and SGT: a new database for structural floor plan analysis and its groundtruthing tool |
Type |
Journal Article |
Year |
2015 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
Volume |
18 |
Issue ![sorted by Issue field, ascending order (up)](img/sort_asc.gif) |
1 |
Pages |
15-30 |
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Abstract |
Recent results on structured learning methods have shown the impact of structural information in a wide range of pattern recognition tasks. In the field of document image analysis, there is a long experience on structural methods for the analysis and information extraction of multiple types of documents. Yet, the lack of conveniently annotated and free access databases has not benefited the progress in some areas such as technical drawing understanding. In this paper, we present a floor plan database, named CVC-FP, that is annotated for the architectural objects and their structural relations. To construct this database, we have implemented a groundtruthing tool, the SGT tool, that allows to make specific this sort of information in a natural manner. This tool has been made for general purpose groundtruthing: It allows to define own object classes and properties, multiple labeling options are possible, grants the cooperative work, and provides user and version control. We finally have collected some of the recent work on floor plan interpretation and present a quantitative benchmark for this database. Both CVC-FP database and the SGT tool are freely released to the research community to ease comparisons between methods and boost reproducible research. |
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Springer Berlin Heidelberg |
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1433-2833 |
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DAG; ADAS; 600.061; 600.076; 600.077 |
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no |
Call Number |
Admin @ si @ HRR2015 |
Serial |
2567 |
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Author |
Miguel Angel Bautista; Antonio Hernandez; Sergio Escalera; Laura Igual; Oriol Pujol; Josep Moya; Veronica Violant; Maria Teresa Anguera |
Title |
A Gesture Recognition System for Detecting Behavioral Patterns of ADHD |
Type |
Journal Article |
Year |
2016 |
Publication |
IEEE Transactions on System, Man and Cybernetics, Part B |
Abbreviated Journal |
TSMCB |
Volume |
46 |
Issue ![sorted by Issue field, ascending order (up)](img/sort_asc.gif) |
1 |
Pages |
136-147 |
Keywords |
Gesture Recognition; ADHD; Gaussian Mixture Models; Convex Hulls; Dynamic Time Warping; Multi-modal RGB-Depth data |
Abstract |
We present an application of gesture recognition using an extension of Dynamic Time Warping (DTW) to recognize behavioural patterns of Attention Deficit Hyperactivity Disorder (ADHD). We propose an extension of DTW using one-class classifiers in order to be able to encode the variability of a gesture category, and thus, perform an alignment between a gesture sample and a gesture class. We model the set of gesture samples of a certain gesture category using either GMMs or an approximation of Convex Hulls. Thus, we add a theoretical contribution to classical warping path in DTW by including local modeling of intra-class gesture variability. This methodology is applied in a clinical context, detecting a group of ADHD behavioural patterns defined by experts in psychology/psychiatry, to provide support to clinicians in the diagnose procedure. The proposed methodology is tested on a novel multi-modal dataset (RGB plus Depth) of ADHD children recordings with behavioural patterns. We obtain satisfying results when compared to standard state-of-the-art approaches in the DTW context. |
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HuPBA; MILAB; |
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no |
Call Number |
Admin @ si @ BHE2016 |
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2566 |
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Author |
Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil |
Title |
A Novel Cochlear Reference Frame Based On The Laplace Equation |
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Conference Article |
Year |
2015 |
Publication |
29th international Congress and Exhibition on Computer Assisted Radiology and Surgery |
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10 |
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1 |
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1-312 |
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Abstract |
Poster |
Address |
Barcelona; Spain; June 2015 |
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CARS |
Notes |
IAM; 600.075 |
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no |
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Admin @ si @ VGG2015 |
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2615 |
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Author |
Marc Bolaños; Mariella Dimiccoli; Petia Radeva |
Title |
Towards Storytelling from Visual Lifelogging: An Overview |
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Journal Article |
Year |
2017 |
Publication |
IEEE Transactions on Human-Machine Systems |
Abbreviated Journal |
THMS |
Volume |
47 |
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1 |
Pages |
77 - 90 |
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Abstract |
Visual lifelogging consists of acquiring images that capture the daily experiences of the user by wearing a camera over a long period of time. The pictures taken offer considerable potential for knowledge mining concerning how people live their lives, hence, they open up new opportunities for many potential applications in fields including healthcare, security, leisure and
the quantified self. However, automatically building a story from a huge collection of unstructured egocentric data presents major challenges. This paper provides a thorough review of advances made so far in egocentric data analysis, and in view of the current state of the art, indicates new lines of research to move us towards storytelling from visual lifelogging. |
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MILAB; 601.235 |
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no |
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Admin @ si @ BDR2017 |
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2712 |
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Author |
Antonio Hernandez; Sergio Escalera; Stan Sclaroff |
Title |
Poselet-basedContextual Rescoring for Human Pose Estimation via Pictorial Structures |
Type |
Journal Article |
Year |
2016 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
Volume |
118 |
Issue ![sorted by Issue field, ascending order (up)](img/sort_asc.gif) |
1 |
Pages |
49–64 |
Keywords |
Contextual rescoring; Poselets; Human pose estimation |
Abstract |
In this paper we propose a contextual rescoring method for predicting the position of body parts in a human pose estimation framework. A set of poselets is incorporated in the model, and their detections are used to extract spatial and score-related features relative to other body part hypotheses. A method is proposed for the automatic discovery of a compact subset of poselets that covers the different poses in a set of validation images while maximizing precision. A rescoring mechanism is defined as a set-based boosting classifier that computes a new score for each body joint detection, given its relationship to detections of other body joints and mid-level parts in the image. This new score is incorporated in the pictorial structure model as an additional unary potential, following the recent work of Pishchulin et al. Experiments on two benchmarks show comparable results to Pishchulin et al. while reducing the size of the mid-level representation by an order of magnitude, reducing the execution time by 68 % accordingly. |
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Springer US |
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0920-5691 |
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HuPBA;MILAB; |
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no |
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Admin @ si @ HES2016 |
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2719 |
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Author |
Isabelle Guyon; Imad Chaabane; Hugo Jair Escalante; Sergio Escalera; Damir Jajetic; James Robert Lloyd; Nuria Macia; Bisakha Ray; Lukasz Romaszko; Michele Sebag; Alexander Statnikov; Sebastien Treguer; Evelyne Viegas |
Title |
A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention |
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Conference Article |
Year |
2016 |
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AutoML Workshop |
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1 |
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1-8 |
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AutoML Challenge; machine learning; model selection; meta-learning; repre- sentation learning; active learning |
Abstract |
The ChaLearn AutoML Challenge team conducted a large scale evaluation of fully automatic, black-box learning machines for feature-based classification and regression problems. The test bed was composed of 30 data sets from a wide variety of application domains and ranged across different types of complexity. Over six rounds, participants succeeded in delivering AutoML software capable of being trained and tested without human intervention. Although improvements can still be made to close the gap between human-tweaked and AutoML models, this competition contributes to the development of fully automated environments by challenging practitioners to solve problems under specific constraints and sharing their approaches; the platform will remain available for post-challenge submissions at http://codalab.org/AutoML. |
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New York; USA; June 2016 |
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ICML |
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HuPBA;MILAB |
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no |
Call Number |
Admin @ si @ GCE2016 |
Serial |
2769 |
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