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Author David Augusto Rojas; Joost Van de Weijer; Theo Gevers
Title Color Edge Saliency Boosting using Natural Image Statistics Type Conference Article
Year 2010 Publication 5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science Abbreviated Journal
Volume Issue Pages 228–234
Keywords
Abstract State of the art methods for image matching, content-based retrieval and recognition use local features. Most of these still exploit only the luminance information for detection. The color saliency boosting algorithm has provided an efficient method to exploit the saliency of color edges based on information theory. However, during the design of this algorithm, some issues were not addressed in depth: (1) The method has ignored the underlying distribution of derivatives in natural images. (2) The dependence of information content in color-boosted edges on its spatial derivatives has not been quantitatively established. (3) To evaluate luminance and color contributions to saliency of edges, a parameter gradually balancing both contributions is required.
We introduce a novel algorithm, based on the principles of independent component analysis, which models the first order derivatives of color natural images by a generalized Gaussian distribution. Furthermore, using this probability model we show that for images with a Laplacian distribution, which is a particular case of generalized Gaussian distribution, the magnitudes of color-boosted edges reflect their corresponding information content. In order to evaluate the impact of color edge saliency in real world applications, we introduce an extension of the Laplacian-of-Gaussian detector to color, and the performance for image matching is evaluated. Our experiments show that our approach provides more discriminative regions in comparison with the original detector.
Address Joensuu, Finland
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN 9781617388897 Medium
Area Expedition Conference CGIV/MCS
Notes ISE Approved no
Call Number CAT @ cat @ RWG2010 Serial 1306
Permanent link to this record
 
 
Author Jaime Moreno; Xavier Otazu; Maria Vanrell
Title Local Perceptual Weighting in JPEG2000 for Color Images Type Conference Article
Year 2010 Publication 5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science Abbreviated Journal
Volume Issue Pages 255–260
Keywords
Abstract The aim of this work is to explain how to apply perceptual concepts to define a perceptual pre-quantizer and to improve JPEG2000 compressor. The approach consists in quantizing wavelet transform coefficients using some of the human visual system behavior properties. Noise is fatal to image compression performance, because it can be both annoying for the observer and consumes excessive bandwidth when the imagery is transmitted. Perceptual pre-quantization reduces unperceivable details and thus improve both visual impression and transmission properties. The comparison between JPEG2000 without and with perceptual pre-quantization shows that the latter is not favorable in PSNR, but the recovered image is more compressed at the same or even better visual quality measured with a weighted PSNR. Perceptual criteria were taken from the CIWaM (Chromatic Induction Wavelet Model).
Address Joensuu, Finland
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN 9781617388897 Medium
Area Expedition Conference CGIV/MCS
Notes CIC Approved no
Call Number CAT @ cat @ MOV2010a Serial 1307
Permanent link to this record
 
 
Author Jaime Moreno; Xavier Otazu; Maria Vanrell
Title Contribution of CIWaM in JPEG2000 Quantization for Color Images Type Conference Article
Year 2010 Publication Proceedings of The CREATE 2010 Conference Abbreviated Journal
Volume Issue Pages 132–136
Keywords
Abstract The aim of this work is to explain how to apply perceptual concepts to define a perceptual pre-quantizer and to improve JPEG2000 compressor. The approach consists in quantizing wavelet transform coefficients using some of the human visual system behavior properties. Noise is fatal to image compression performance, because it can be both annoying for the observer and consumes excessive bandwidth when the imagery is transmitted. Perceptual pre-quantization reduces unperceivable details and thus improve both visual impression and transmission properties. The comparison between JPEG2000 without and with perceptual pre-quantization shows that the latter is not favorable in PSNR, but the recovered image is more compressed at the same or even better visual quality measured with a weighted PSNR. Perceptual criteria were taken from the CIWaM(ChromaticInductionWaveletModel).
Address Gjovik (Norway)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CREATE
Notes CIC Approved no
Call Number CAT @ cat @ MOV2010b Serial 1308
Permanent link to this record
 
 
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 (up)
Series Volume Series Issue Edition
ISSN 2160-7508 ISBN 978-1-4244-7029-7 Medium
Area Expedition Conference CVPRW
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ DoR2010a Serial 1309
Permanent link to this record
 
 
Author Bogdan Raducanu; Fadi Dornaika
Title Dynamic Facial Expression Recognition Using Laplacian Eigenmaps-Based Manifold Learning Type Conference Article
Year 2010 Publication IEEE International Conference on Robotics and Automation Abbreviated Journal
Volume Issue Pages 156–161
Keywords
Abstract In this paper, we propose an integrated framework for tracking, modelling and recognition of facial expressions. The main contributions are: (i) a view- and texture independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker; (ii) the complexity of the non-linear facial expression space is modelled through a manifold, whose structure is learned using Laplacian Eigenmaps. The projected facial expressions are afterwards recognized based on Nearest Neighbor classifier; (iii) with the proposed approach, we developed an application for an AIBO robot, in which it mirrors the perceived facial expression.
Address Anchorage; AK; USA;
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN 1050-4729 ISBN 978-1-4244-5038-1 Medium
Area Expedition Conference ICRA
Notes OR; MV Approved no
Call Number BCNPCL @ bcnpcl @ RaD2010 Serial 1310
Permanent link to this record
 
 
Author David Aldavert; Arnau Ramisa; Ramon Lopez de Mantaras; Ricardo Toledo
Title Fast and Robust Object Segmentation with the Integral Linear Classifier Type Conference Article
Year 2010 Publication 23rd IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages 1046–1053
Keywords
Abstract We propose an efficient method, built on the popular Bag of Features approach, that obtains robust multiclass pixel-level object segmentation of an image in less than 500ms, with results comparable or better than most state of the art methods. We introduce the Integral Linear Classifier (ILC), that can readily obtain the classification score for any image sub-window with only 6 additions and 1 product by fusing the accumulation and classification steps in a single operation. In order to design a method as efficient as possible, our building blocks are carefully selected from the quickest in the state of the art. More precisely, we evaluate the performance of three popular local descriptors, that can be very efficiently computed using integral images, and two fast quantization methods: the Hierarchical K-Means, and the Extremely Randomized Forest. Finally, we explore the utility of adding spatial bins to the Bag of Features histograms and that of cascade classifiers to improve the obtained segmentation. Our method is compared to the state of the art in the difficult Graz-02 and PASCAL 2007 Segmentation Challenge datasets.
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 (up)
Series Volume Series Issue Edition
ISSN 1063-6919 ISBN 978-1-4244-6984-0 Medium
Area Expedition Conference CVPR
Notes ADAS Approved no
Call Number Admin @ si @ ARL2010a Serial 1311
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Author Simone Balocco; O. Basset; G. Courbebaisse; E. Boni; Alejandro F. Frangi; P. Tortoli; C. Cachard
Title Estimation Of Viscoelastic Properties Of Vessel Walls Using a Computational Model and Doppler Ultrasound Type Journal Article
Year 2010 Publication Physics in Medicine and Biology Abbreviated Journal PMB
Volume 55 Issue 12 Pages 3557–3575
Keywords
Abstract Human arteries affected by atherosclerosis are characterized by altered wall viscoelastic properties. The possibility of noninvasively assessing arterial viscoelasticity in vivo would significantly contribute to the early diagnosis and prevention of this disease. This paper presents a noniterative technique to estimate the viscoelastic parameters of a vascular wall Zener model. The approach requires the simultaneous measurement of flow variations and wall displacements, which can be provided by suitable ultrasound Doppler instruments. Viscoelastic parameters are estimated by fitting the theoretical constitutive equations to the experimental measurements using an ARMA parameter approach. The accuracy and sensitivity of the proposed method are tested using reference data generated by numerical simulations of arterial pulsation in which the physiological conditions and the viscoelastic parameters of the model can be suitably varied. The estimated values quantitatively agree with the reference values, showing that the only parameter affected by changing the physiological conditions is viscosity, whose relative error was about 27% even when a poor signal-to-noise ratio is simulated. Finally, the feasibility of the method is illustrated through three measurements made at different flow regimes on a cylindrical vessel phantom, yielding a parameter mean estimation error of 25%.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ BBC2010 Serial 1312
Permanent link to this record
 
 
Author Simone Balocco; O. Camara; E. Vivas; T. Sola; L. Guimaraens; H. A. van Andel; C. B. Majoie; J. M. Pozo; B. H. Bijnens; Alejandro F. Frangi
Title Feasibility of Estimating Regional Mechanical Properties of Cerebral Aneurysms In Vivo Type Journal Article
Year 2010 Publication Medical Physics Abbreviated Journal MEDPHYS
Volume 37 Issue 4 Pages 1689–1706
Keywords
Abstract PURPOSE:
In this article, the authors studied the feasibility of estimating regional mechanical properties in cerebral aneurysms, integrating information extracted from imaging and physiological data with generic computational models of the arterial wall behavior.
METHODS:
A data assimilation framework was developed to incorporate patient-specific geometries into a given biomechanical model, whereas wall motion estimates were obtained from applying registration techniques to a pair of simulated MR images and guided the mechanical parameter estimation. A simple incompressible linear and isotropic Hookean model coupled with computational fluid-dynamics was employed as a first approximation for computational purposes. Additionally, an automatic clustering technique was developed to reduce the number of parameters to assimilate at the optimization stage and it considerably accelerated the convergence of the simulations. Several in silico experiments were designed to assess the influence of aneurysm geometrical characteristics and the accuracy of wall motion estimates on the mechanical property estimates. Hence, the proposed methodology was applied to six real cerebral aneurysms and tested against a varying number of regions with different elasticity, different mesh discretization, imaging resolution, and registration configurations.
RESULTS:
Several in silico experiments were conducted to investigate the feasibility of the proposed workflow, results found suggesting that the estimation of the mechanical properties was mainly influenced by the image spatial resolution and the chosen registration configuration. According to the in silico experiments, the minimal spatial resolution needed to extract wall pulsation measurements with enough accuracy to guide the proposed data assimilation framework was of 0.1 mm.
CONCLUSIONS:
Current routine imaging modalities do not have such a high spatial resolution and therefore the proposed data assimilation framework cannot currently be used on in vivo data to reliably estimate regional properties in cerebral aneurysms. Besides, it was observed that the incorporation of fluid-structure interaction in a biomechanical model with linear and isotropic material properties did not have a substantial influence in the final results.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ BCV2010 Serial 1313
Permanent link to this record
 
 
Author Simone Balocco; Carlo Gatta; Oriol Pujol; J. Mauri; Petia Radeva
Title SRBF: Speckle Reducing Bilateral Filtering Type Journal Article
Year 2010 Publication Ultrasound in Medicine and Biology Abbreviated Journal UMB
Volume 36 Issue 8 Pages 1353-1363
Keywords
Abstract Speckle noise negatively affects medical ultrasound image shape interpretation and boundary detection. Speckle removal filters are widely used to selectively remove speckle noise without destroying important image features to enhance object boundaries. In this article, a fully automatic bilateral filter tailored to ultrasound images is proposed. The edge preservation property is obtained by embedding noise statistics in the filter framework. Consequently, the filter is able to tackle the multiplicative behavior modulating the smoothing strength with respect to local statistics. The in silico experiments clearly showed that the speckle reducing bilateral filter (SRBF) has superior performances to most of the state of the art filtering methods. The filter is tested on 50 in vivo US images and its influence on a segmentation task is quantified. The results using SRBF filtered data sets show a superior performance to using oriented anisotropic diffusion filtered images. This improvement is due to the adaptive support of SRBF and the embedded noise statistics, yielding a more homogeneous smoothing. SRBF results in a fully automatic, fast and flexible algorithm potentially suitable in wide ranges of speckle noise sizes, for different medical applications (IVUS, B-mode, 3-D matrix array US).
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MILAB;HUPBA Approved no
Call Number BCNPCL @ bcnpcl @ BGP2010 Serial 1314
Permanent link to this record
 
 
Author Sergio Escalera; R. M. Martinez; Jordi Vitria; Petia Radeva; Maria Teresa Anguera
Title Deteccion automatica de la dominancia en conversaciones diadicas Type Journal Article
Year 2010 Publication Escritos de Psicologia Abbreviated Journal EP
Volume 3 Issue 2 Pages 41–45
Keywords Dominance detection; Non-verbal communication; Visual features
Abstract Dominance is referred to the level of influence that a person has in a conversation. Dominance is an important research area in social psychology, but the problem of its automatic estimation is a very recent topic in the contexts of social and wearable computing. In this paper, we focus on the dominance detection of visual cues. We estimate the correlation among observers by categorizing the dominant people in a set of face-to-face conversations. Different dominance indicators from gestural communication are defined, manually annotated, and compared to the observers' opinion. Moreover, these indicators are automatically extracted from video sequences and learnt by using binary classifiers. Results from the three analyses showed a high correlation and allows the categorization of dominant people in public discussion video sequences.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN 1989-3809 ISBN Medium
Area Expedition Conference
Notes HUPBA; OR; MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ EMV2010 Serial 1315
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Author Michal Drozdzal; Laura Igual; Petia Radeva; Jordi Vitria; C. 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 (up)
Series Volume Series Issue Edition
ISSN 2160-7508 ISBN 978-1-4244-7029-7 Medium
Area Expedition Conference MMBIA
Notes OR;MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ DIR2010 Serial 1316
Permanent link to this record
 
 
Author Wenjuan Gong; Andrew Bagdanov; Xavier Roca; Jordi Gonzalez
Title Automatic Key Pose Selection for 3D Human Action Recognition Type Conference Article
Year 2010 Publication 6th International Conference on Articulated Motion and Deformable Objects Abbreviated Journal
Volume 6169 Issue Pages 290–299
Keywords
Abstract This article describes a novel approach to the modeling of human actions in 3D. The method we propose is based on a “bag of poses” model that represents human actions as histograms of key-pose occurrences over the course of a video sequence. Actions are first represented as 3D poses using a sequence of 36 direction cosines corresponding to the angles 12 joints form with the world coordinate frame in an articulated human body model. These pose representations are then projected to three-dimensional, action-specific principal eigenspaces which we refer to as aSpaces. We introduce a method for key-pose selection based on a local-motion energy optimization criterion and we show that this method is more stable and more resistant to noisy data than other key-poses selection criteria for action recognition.
Address
Corporate Author Thesis
Publisher Springer Verlag Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-14060-0 Medium
Area Expedition Conference AMDO
Notes ISE Approved no
Call Number DAG @ dag @ GBR2010 Serial 1317
Permanent link to this record
 
 
Author Alicia Fornes; Josep Llados; Gemma Sanchez; Xavier Otazu; Horst Bunke
Title A Combination of Features for Symbol-Independent Writer Identification in Old Music Scores Type Journal Article
Year 2010 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 13 Issue 4 Pages 243-259
Keywords
Abstract The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper, we present an architecture for writer identification in old handwritten music scores. Even though an important amount of music compositions contain handwritten text, the aim of our work is to use only music notation to determine the author. The main contribution is therefore the use of features extracted from graphical alphabets. Our proposal consists in combining the identification results of two different approaches, based on line and textural features. The steps of the ensemble architecture are the following. First of all, the music sheet is preprocessed for removing the staff lines. Then, music lines and texture images are generated for computing line features and textural features. Finally, the classification results are combined for identifying the writer. The proposed method has been tested on a database of old music scores from the seventeenth to nineteenth centuries, achieving a recognition rate of about 92% with 20 writers.
Address
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN 1433-2833 ISBN Medium
Area Expedition Conference
Notes DAG; CAT;CIC Approved no
Call Number FLS2010b Serial 1319
Permanent link to this record
 
 
Author Albert Gordo; Alicia Fornes; Ernest Valveny; Josep Llados
Title A Bag of Notes Approach to Writer Identification in Old Handwritten Music Scores Type Conference Article
Year 2010 Publication 9th IAPR International Workshop on Document Analysis Systems Abbreviated Journal
Volume Issue Pages 247–254
Keywords
Abstract Determining the authorship of a document, namely writer identification, can be an important source of information for document categorization. Contrary to text documents, the identification of the writer of graphical documents is still a challenge. In this paper we present a robust approach for writer identification in a particular kind of graphical documents, old music scores. This approach adapts the bag of visual terms method for coping with graphic documents. The identification is performed only using the graphical music notation. For this purpose, we generate a graphic vocabulary without recognizing any music symbols, and consequently, avoiding the difficulties in the recognition of hand-drawn symbols in old and degraded documents. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving very high identification rates.
Address Boston; USA;
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN 978-1-60558-773-8 Medium
Area Expedition Conference DAS
Notes DAG Approved no
Call Number DAG @ dag @ GFV2010 Serial 1320
Permanent link to this record
 
 
Author Alicia Fornes; Josep Llados
Title A Symbol-dependent Writer Identifcation Approach in Old Handwritten Music Scores Type Conference Article
Year 2010 Publication 12th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal
Volume Issue Pages 634 - 639
Keywords
Abstract Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we introduce a symbol-dependent approach for identifying the writer of old music scores, which is based on two symbol recognition methods. The main idea is to use the Blurred Shape Model descriptor and a DTW-based method for detecting, recognizing and describing the music clefs and notes. The proposed approach has been evaluated in a database of old music scores, achieving very high writer identification rates.
Address Kolkata (India)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN 978-1-4244-8353-2 Medium
Area Expedition Conference ICFHR
Notes DAG Approved no
Call Number DAG @ dag @ FoL2010 Serial 1321
Permanent link to this record