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Author Mario Rojas; David Masip; Jordi Vitria
Title Predicting Dominance Judgements Automatically: A Machine Learning Approach. Type Conference Article
Year 2011 Publication IEEE International Workshop on Social Behavior Analysis Abbreviated Journal
Volume Issue Pages 939-944
Keywords
Abstract The amount of multimodal devices that surround us is growing everyday. In this context, human interaction and communication have become a focus of attention and a hot topic of research. A crucial element in human relations is the evaluation of individuals with respect to facial traits, what is called a first impression. Studies based on appearance have suggested that personality can be expressed by appearance and the observer may use such information to form judgments. In the context of rapid facial evaluation, certain personality traits seem to have a more pronounced effect on the relations and perceptions inside groups. The perception of dominance has been shown to be an active part of social roles at different stages of life, and even play a part in mate selection. The aim of this paper is to study to what extent this information is learnable from the point of view of computer science. Specifically we intend to determine if judgments of dominance can be learned by machine learning techniques. We implement two different descriptors in order to assess this. The first is the histogram of oriented gradients (HOG), and the second is a probabilistic appearance descriptor based on the frequencies of grouped binary tests. State of the art classification rules validate the performance of both descriptors, with respect to the prediction task. Experimental results show that machine learning techniques can predict judgments of dominance rather accurately (accuracies up to 90%) and that the HOG descriptor may characterize appropriately the information necessary for such task.
Address Santa Barbara, CA
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 (down) 978-1-4244-9140-7 Medium
Area Expedition Conference SBA
Notes OR;MV Approved no
Call Number Admin @ si @ RMV2011b Serial 1760
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Author Murad Al Haj; Carles Fernandez; Zhanwu Xiong; Ivan Huerta; Jordi Gonzalez; Xavier Roca
Title Beyond the Static Camera: Issues and Trends in Active Vision Type Book Chapter
Year 2011 Publication Visual Analysis of Humans: Looking at People Abbreviated Journal
Volume Issue 2 Pages 11-30
Keywords
Abstract Maximizing both the area coverage and the resolution per target is highly desirable in many applications of computer vision. However, with a limited number of cameras viewing a scene, the two objectives are contradictory. This chapter is dedicated to active vision systems, trying to achieve a trade-off between these two aims and examining the use of high-level reasoning in such scenarios. The chapter starts by introducing different approaches to active cameras configurations. Later, a single active camera system to track a moving object is developed, offering the reader first-hand understanding of the issues involved. Another section discusses practical considerations in building an active vision platform, taking as an example a multi-camera system developed for a European project. The last section of the chapter reflects upon the future trends of using semantic factors to drive smartly coordinated active systems.
Address
Corporate Author Thesis
Publisher Springer London Place of Publication Editor Th.B. Moeslund; A. Hilton; V. Krüger; L. Sigal
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (down) 978-0-85729-996-3 Medium
Area Expedition Conference
Notes ISE Approved no
Call Number Admin @ si @ AFX2011 Serial 1814
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Author Nataliya Shapovalova; Carles Fernandez; Xavier Roca; Jordi Gonzalez
Title Semantics of Human Behavior in Image Sequences Type Book Chapter
Year 2011 Publication Computer Analysis of Human Behavior Abbreviated Journal
Volume Issue 7 Pages 151-182
Keywords
Abstract Human behavior is contextualized and understanding the scene of an action is crucial for giving proper semantics to behavior. In this chapter we present a novel approach for scene understanding. The emphasis of this work is on the particular case of Human Event Understanding. We introduce a new taxonomy to organize the different semantic levels of the Human Event Understanding framework proposed. Such a framework particularly contributes to the scene understanding domain by (i) extracting behavioral patterns from the integrative analysis of spatial, temporal, and contextual evidence and (ii) integrative analysis of bottom-up and top-down approaches in Human Event Understanding. We will explore how the information about interactions between humans and their environment influences the performance of activity recognition, and how this can be extrapolated to the temporal domain in order to extract higher inferences from human events observed in sequences of images.
Address
Corporate Author Thesis
Publisher Springer London Place of Publication Editor Albert Ali Salah;
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (down) 978-0-85729-993-2 Medium
Area Expedition Conference
Notes ISE Approved no
Call Number Admin @ si @ SFR2011 Serial 1810
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Author Jon Almazan; Alicia Fornes; Ernest Valveny
Title A Non-Rigid Feature Extraction Method for Shape Recognition Type Conference Article
Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 987-991
Keywords
Abstract This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm. Then, a feature vector is extracted by computing pixel density measures around these geometrical centroids. The result is a shape descriptor that adapts its representation to the given shape and encodes the pixel density distribution. The validity of the method when dealing with large deformations has been experimentally shown over datasets composed of handwritten shapes. It has been applied to signature verification and shape recognition tasks demonstrating high accuracy and low computational cost.
Address Beijing; China; September 2011
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 (down) 978-0-7695-4520-2 Medium
Area Expedition Conference ICDAR
Notes DAG Approved no
Call Number Admin @ si @ AFV2011 Serial 1763
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Author Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny
Title Wall Patch-Based Segmentation in Architectural Floorplans Type Conference Article
Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 1270-1274
Keywords
Abstract Segmentation of architectural floor plans is a challenging task, mainly because of the large variability in the notation between different plans. In general, traditional techniques, usually based on analyzing and grouping structural primitives obtained by vectorization, are only able to handle a reduced range of similar notations. In this paper we propose an alternative patch-based segmentation approach working at pixel level, without need of vectorization. The image is divided into a set of patches and a set of features is extracted for every patch. Then, each patch is assigned to a visual word of a previously learned vocabulary and given a probability of belonging to each class of objects. Finally, a post-process assigns the final label for every pixel. This approach has been applied to the detection of walls on two datasets of architectural floor plans with different notations, achieving high accuracy rates.
Address Beiging, 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 1520-5363 ISBN (down) 978-0-7695-4520-2 Medium
Area Expedition Conference ICDAR
Notes DAG Approved no
Call Number Admin @ si @ HMS2011a Serial 1792
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Author Alicia Fornes; Anjan Dutta; Albert Gordo; Josep Llados
Title The ICDAR 2011 Music Scores Competition: Staff Removal and Writer Identification Type Conference Article
Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 1511-1515
Keywords
Abstract In the last years, there has been a growing interest in the analysis of handwritten music scores. In this sense, our goal has been to foster the interest in the analysis of handwritten music scores by the proposal of two different competitions: Staff removal and Writer Identification. Both competitions have been tested on the CVC-MUSCIMA database: a ground-truth of handwritten music score images. This paper describes the competition details, including the dataset and ground-truth, the evaluation metrics, and a short description of the participants, their methods, and the obtained results.
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 (down) 978-0-7695-4520-2 Medium
Area Expedition Conference ICDAR
Notes DAG Approved no
Call Number Admin @ si @ FDG2011b Serial 1794
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Author Mariano Vazquez; Ruth Aris; Guillaume Hozeaux; R.Aubry; P.Villar;Jaume Garcia ; Debora Gil; Francesc Carreras
Title A massively parallel computational electrophysiology model of the heart Type Journal Article
Year 2011 Publication International Journal for Numerical Methods in Biomedical Engineering Abbreviated Journal IJNMBE
Volume 27 Issue Pages 1911-1929
Keywords computational electrophysiology; parallelization; finite element methods
Abstract This paper presents a patient-sensitive simulation strategy capable of using the most efficient way the high-performance computational resources. The proposed strategy directly involves three different players: Computational Mechanics Scientists (CMS), Image Processing Scientists and Cardiologists, each one mastering its own expertise area within the project. This paper describes the general integrative scheme but focusing on the CMS side presents a massively parallel implementation of computational electrophysiology applied to cardiac tissue simulation. The paper covers different angles of the computational problem: equations, numerical issues, the algorithm and parallel implementation. The proposed methodology is illustrated with numerical simulations testing all the different possibilities, ranging from small domains up to very large ones. A key issue is the almost ideal scalability not only for large and complex problems but also for medium-size meshes. The explicit formulation is particularly well suited for solving this highly transient problems, with very short time-scale.
Address Swansea (UK)
Corporate Author John Wiley & Sons, Ltd. Thesis
Publisher John Wiley & Sons, Ltd. Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (down) Medium
Area Expedition Conference
Notes IAM Approved no
Call Number IAM @ iam @ VAH2011 Serial 1198
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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 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.
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 (down) Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ PSL2011 Serial 1413
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Author Jose Manuel Alvarez; Antonio Lopez
Title Road Detection Based on Illuminant Invariance Type Journal Article
Year 2011 Publication IEEE Transactions on Intelligent Transportation Systems Abbreviated Journal TITS
Volume 12 Issue 1 Pages 184-193
Keywords road detection
Abstract By using an onboard camera, it is possible to detect the free road surface ahead of the ego-vehicle. Road detection is of high relevance for autonomous driving, road departure warning, and supporting driver-assistance systems such as vehicle and pedestrian detection. The key for vision-based road detection is the ability to classify image pixels as belonging or not to the road surface. Identifying road pixels is a major challenge due to the intraclass variability caused by lighting conditions. A particularly difficult scenario appears when the road surface has both shadowed and nonshadowed areas. Accordingly, we propose a novel approach to vision-based road detection that is robust to shadows. The novelty of our approach relies on using a shadow-invariant feature space combined with a model-based classifier. The model is built online to improve the adaptability of the algorithm to the current lighting and the presence of other vehicles in the scene. The proposed algorithm works in still images and does not depend on either road shape or temporal restrictions. Quantitative and qualitative experiments on real-world road sequences with heavy traffic and shadows show that the method is robust to shadows and lighting variations. Moreover, the proposed method provides the highest performance when compared with hue-saturation-intensity (HSI)-based algorithms.
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 (down) Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ AlL2011 Serial 1456
Permanent link to this record
 
 
Author Debora Gil; Aura Hernandez-Sabate; Mireia Brunat;Steven Jansen; Jordi Martinez-Vilalta
Title Structure-preserving smoothing of biomedical images Type Journal Article
Year 2011 Publication Pattern Recognition Abbreviated Journal PR
Volume 44 Issue 9 Pages 1842-1851
Keywords Non-linear smoothing; Differential geometry; Anatomical structures; segmentation; Cardiac magnetic resonance; Computerized tomography
Abstract Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images.
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 0031-3203 ISBN (down) Medium
Area Expedition Conference
Notes IAM; ADAS Approved no
Call Number IAM @ iam @ GHB2011 Serial 1526
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Author Aura Hernandez-Sabate; Debora Gil; Jaume Garcia; Enric Marti
Title Image-based Cardiac Phase Retrieval in Intravascular Ultrasound Sequences Type Journal Article
Year 2011 Publication IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control Abbreviated Journal T-UFFC
Volume 58 Issue 1 Pages 60-72
Keywords 3-D exploring; ECG; band-pass filter; cardiac motion; cardiac phase retrieval; coronary arteries; electrocardiogram signal; image intensity local mean evolution; image-based cardiac phase retrieval; in vivo pullbacks acquisition; intravascular ultrasound sequences; longitudinal motion; signal extrema; time 36 ms; band-pass filters; biomedical ultrasonics; cardiovascular system; electrocardiography; image motion analysis; image retrieval; image sequences; medical image processing; ultrasonic imaging
Abstract Longitudinal motion during in vivo pullbacks acquisition of intravascular ultrasound (IVUS) sequences is a major artifact for 3-D exploring of coronary arteries. Most current techniques are based on the electrocardiogram (ECG) signal to obtain a gated pullback without longitudinal motion by using specific hardware or the ECG signal itself. We present an image-based approach for cardiac phase retrieval from coronary IVUS sequences without an ECG signal. A signal reflecting cardiac motion is computed by exploring the image intensity local mean evolution. The signal is filtered by a band-pass filter centered at the main cardiac frequency. Phase is retrieved by computing signal extrema. The average frame processing time using our setup is 36 ms. Comparison to manually sampled sequences encourages a deeper study comparing them to ECG signals.
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 0885-3010 ISBN (down) Medium
Area Expedition Conference
Notes IAM;ADAS Approved no
Call Number IAM @ iam @ HGG2011 Serial 1546
Permanent link to this record
 
 
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 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 (down) Medium
Area Expedition Conference CAIP
Notes IAM; ADAS Approved no
Call Number IAM @ iam @ HGR2011 Serial 1676
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Author David Roche; Debora Gil; Jesus Giraldo
Title Using statistical inference for designing termination conditions ensuring convergence of Evolutionary Algorithms Type Conference Article
Year 2011 Publication 11th European Conference on Artificial Life Abbreviated Journal
Volume Issue Pages
Keywords
Abstract A main challenge in Evolutionary Algorithms (EAs) is determining a termination condition ensuring stabilization close to the optimum in real-world applications. Although for known test functions distribution-based quantities are good candidates (as far as suitable parameters are used), in real-world problems an open question still remains unsolved. How can we estimate an upper-bound for the termination condition value ensuring a given accuracy for the (unknown) EA solution?
We claim that the termination problem would be fully solved if we defined a quantity (depending only on the EA output) behaving like the solution accuracy. The open question would be, then, satisfactorily answered if we had a model relating both quantities, since accuracy could be predicted from the alternative quantity. We present a statistical inference framework addressing two topics: checking the correlation between the two quantities and defining a regression model for predicting (at a given confidence level) accuracy values from the EA output.
Address Paris, France
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 (down) Medium
Area Expedition Conference ECAL
Notes IAM; Approved no
Call Number IAM @ iam @ RGG2011b Serial 1678
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Author Ferran Poveda; Debora Gil ;Albert Andaluz ;Enric Marti
Title Multiscale Tractography for Representing Heart Muscular Architecture Type Conference Article
Year 2011 Publication In MICCAI 2011 Workshop on Computational Diffusion MRI Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. Although the muscular architecture of the heart has been debated by countless researchers, the controversy is still alive. Diffusion Tensor MRI, DT-MRI, is a unique imaging technique for computational validation of the muscular structure of the heart. By the complex arrangement of myocites, existing techniques can not provide comprehensive descriptions of the global muscular architecture. In this paper we introduce a multiresolution reconstruction technique based on DT-MRI streamlining for simplified global myocardial model generation. Our reconstructions can restore the most complex myocardial structures and indicate a global helical organization
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language english Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (down) Medium
Area Expedition Conference CDRMI
Notes IAM Approved no
Call Number IAM @ iam @ PGA2011 Serial 1681
Permanent link to this record
 
 
Author Patricia Marquez; Debora Gil; Aura Hernandez-Sabate
Title A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth Type Conference Article
Year 2011 Publication IEEE International Conference on Computer Vision – Workshops Abbreviated Journal
Volume Issue Pages 2042-2049
Keywords IEEE International Conference on Computer Vision – Workshops
Abstract Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems.
Address
Corporate Author Thesis
Publisher IEEE Place of Publication Barcelona (Spain) Editor
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (down) Medium
Area Expedition Conference ICCVW
Notes IAM; ADAS Approved no
Call Number IAM @ iam @ MGH2011 Serial 1682
Permanent link to this record