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Author Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados
Title Improving Fuzzy Multilevel Graph Embedding through Feature Selection Technique Type Conference Article
Year 2012 Publication Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop Abbreviated Journal
Volume 7626 Issue Pages 243-253
Keywords
Abstract Graphs are the most powerful, expressive and convenient data structures but there is a lack of efficient computational tools and algorithms for processing them. The embedding of graphs into numeric vector spaces permits them to access the state-of-the-art computational efficient statistical models and tools. In this paper we take forward our work on explicit graph embedding and present an improvement to our earlier proposed method, named “fuzzy multilevel graph embedding – FMGE”, through feature selection technique. FMGE achieves the embedding of attributed graphs into low dimensional vector spaces by performing a multilevel analysis of graphs and extracting a set of global, structural and elementary level features. Feature selection permits FMGE to select the subset of most discriminating features and to discard the confusing ones for underlying graph dataset. Experimental results for graph classification experimentation on IAM letter, GREC and fingerprint graph databases, show improvement in the performance of FMGE.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-34165-6 Medium
Area Expedition Conference SSPR&SPR
Notes DAG Approved no
Call Number Admin @ si @ LRL2012 Serial 2381
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Author Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru; Miguel Angel Gonzalez Ballester
Title Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs Type Book Chapter
Year 2012 Publication Workshop on Computational and Clinical Applications in Abdominal Imaging Abbreviated Journal
Volume 7029 Issue Pages 223–230
Keywords medial manifolds, abdomen.
Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D
objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial
manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our
method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs,
exploring the use of medial manifolds for the representation of multi-organ relations.
Address Toronto; Canada;
Corporate Author Thesis
Publisher Springer Link Place of Publication Berlin Editor H. Yoshida et al
Language English Summary Language English Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-28556-1 Medium
Area Expedition Conference ABDI
Notes IAM;MV Approved no
Call Number IAM @ iam @ VGB2012 Serial 1834
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Author Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil
Title An illumination model of the trachea appearance in videobronchoscopy images Type Book Chapter
Year 2012 Publication Image Analysis and Recognition Abbreviated Journal LNCS
Volume 7325 Issue Pages 313-320
Keywords Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation
Abstract Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error.
This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution.
Address Aveiro, Portugal
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-31297-7 Medium
Area 800 Expedition Conference ICIAR
Notes MV;IAM Approved no
Call Number IAM @ iam @ SSR2012 Serial 1898
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Author Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate
Title Error Analysis for Lucas-Kanade Based Schemes Type Conference Article
Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal
Volume 7324 Issue I Pages 184-191
Keywords Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance
Abstract Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures.
Address Aveiro, Portugal
Corporate Author Thesis
Publisher Springer-Verlag Berlin Heidelberg Place of Publication Editor
Language english Summary Language Original Title
Series Editor Campilho, Aurélio and Kamel, Mohamed Series Title Lecture Notes in Computer Science Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-31294-6 Medium
Area Expedition Conference ICIAR
Notes IAM Approved no
Call Number IAM @ iam @ MGH2012a Serial 1899
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Author Yainuvis Socarras; David Vazquez; Antonio Lopez; David Geronimo; Theo Gevers
Title Improving HOG with Image Segmentation: Application to Human Detection Type Conference Article
Year 2012 Publication 11th International Conference on Advanced Concepts for Intelligent Vision Systems Abbreviated Journal
Volume 7517 Issue Pages 178-189
Keywords Segmentation; Pedestrian Detection
Abstract In this paper we improve the histogram of oriented gradients (HOG), a core descriptor of state-of-the-art object detection, by the use of higher-level information coming from image segmentation. The idea is to re-weight the descriptor while computing it without increasing its size. The benefits of the proposal are two-fold: (i) to improve the performance of the detector by enriching the descriptor information and (ii) take advantage of the information of image segmentation, which in fact is likely to be used in other stages of the detection system such as candidate generation or refinement.
We test our technique in the INRIA person dataset, which was originally developed to test HOG, embedding it in a human detection system. The well-known segmentation method, mean-shift (from smaller to larger super-pixels), and different methods to re-weight the original descriptor (constant, region-luminance, color or texture-dependent) has been evaluated. We achieve performance improvements of 4:47% in detection rate through the use of differences of color between contour pixel neighborhoods as re-weighting function.
Address Brno, Czech Republic
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor J. Blanc-Talon et al.
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-33139-8 Medium
Area Expedition Conference ACIVS
Notes ADAS;ISE Approved no
Call Number ADAS @ adas @ SLV2012 Serial 1980
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Author Ferran Poveda; Debora Gil;Enric Marti
Title Multi-resolution DT-MRI cardiac tractography Type Conference Article
Year 2012 Publication Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges Abbreviated Journal
Volume 7746 Issue Pages 270-277
Keywords
Abstract Even using objective measures from DT-MRI no consensus about myocardial architecture has been achieved so far. Streamlining provides good reconstructions at low level of detail, but falls short to give global abstract interpretations. In this paper, we present a multi-resolution methodology that is able to produce simplified representations of cardiac architecture. Our approach produces a reduced set of tracts that are representative of the main geometric features of myocardial anatomical structure. Experiments show that fiber geometry is preserved along reductions, which validates the simplified model for interpretation of cardiac architecture.
Address Nice, France
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-36960-5 Medium
Area Expedition Conference STACOM
Notes IAM Approved no
Call Number IAM @ iam @ PGM2012 Serial 1986
Permanent link to this record
 

 
Author Patricia Marquez;Debora Gil;Aura Hernandez-Sabate
Title A Complete Confidence Framework for Optical Flow Type Conference Article
Year 2012 Publication 12th European Conference on Computer Vision – Workshops and Demonstrations Abbreviated Journal
Volume 7584 Issue 2 Pages 124-133
Keywords Optical flow, confidence measures, sparsification plots, error prediction plots
Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations.
Address
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Florence, Italy, October 7-13, 2012 Editor Andrea Fusiello, Vittorio Murino ,Rita Cucchiara
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-33867-0 Medium
Area Expedition Conference ECCVW
Notes IAM;ADAS; Approved no
Call Number IAM @ iam @ MGH2012b Serial 1991
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Author Albert Clapes; Miguel Reyes; Sergio Escalera
Title User Identification and Object Recognition in Clutter Scenes Based on RGB-Depth Analysis Type Conference Article
Year 2012 Publication 7th Conference on Articulated Motion and Deformable Objects Abbreviated Journal
Volume 7378 Issue Pages 1-11
Keywords
Abstract We propose an automatic system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized online using robust statistical approaches over RGBD descriptions. Finally, the system saves the historic of user-object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches.
Address Mallorca
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-31566-4 Medium
Area Expedition Conference AMDO
Notes HUPBA;MILAB Approved no
Call Number Admin @ si @ CRE2012 Serial 2010
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Author Fernando Barrera; Felipe Lumbreras; Angel Sappa
Title Evaluation of Similarity Functions in Multimodal Stereo Type Conference Article
Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal
Volume 7324 Issue I Pages 320-329
Keywords Aveiro, Portugal
Abstract This paper presents an evaluation framework for multimodal stereo matching, which allows to compare the performance of four similarity functions. Additionally, it presents details of a multimodal stereo head that supply thermal infrared and color images, as well as, aspects of its calibration and rectification. The pipeline includes a novel method for the disparity selection, which is suitable for evaluating the similarity functions. Finally, a benchmark for comparing different initializations of the proposed framework is presented. Similarity functions are based on mutual information, gradient orientation and scale space representations. Their evaluation is performed using two metrics: i) disparity error, and ii) number of correct matches on planar regions. In addition to the proposed evaluation, the current paper also shows that 3D sparse representations can be recovered from such a multimodal stereo head.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-31294-6 Medium
Area Expedition Conference ICIAR
Notes ADAS Approved no
Call Number BLS2012a Serial 2014
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Author Miguel Oliveira; Angel Sappa; V. Santos
Title Color Correction using 3D Gaussian Mixture Models Type Conference Article
Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal
Volume 7324 Issue I Pages 97-106
Keywords
Abstract The current paper proposes a novel color correction approach based on a probabilistic segmentation framework by using 3D Gaussian Mixture Models. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. The proposed approach is evaluated using both a recently published metric and two large data sets composed of seventy images. The evaluation is performed by comparing our algorithm with eight well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 10.1007/978-3-642-31295-3_12 Medium
Area Expedition Conference ICIAR
Notes ADAS Approved no
Call Number Admin @ si @ OSS2012a Serial 2015
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Author Jose Manuel Alvarez; Theo Gevers; Y. LeCun; Antonio Lopez
Title Road Scene Segmentation from a Single Image Type Conference Article
Year 2012 Publication 12th European Conference on Computer Vision Abbreviated Journal
Volume 7578 Issue VII Pages 376-389
Keywords road detection
Abstract Road scene segmentation is important in computer vision for different applications such as autonomous driving and pedestrian detection. Recovering the 3D structure of road scenes provides relevant contextual information to improve their understanding.
In this paper, we use a convolutional neural network based algorithm to learn features from noisy labels to recover the 3D scene layout of a road image. The novelty of the algorithm relies on generating training labels by applying an algorithm trained on a general image dataset to classify on–board images. Further, we propose a novel texture descriptor based on a learned color plane fusion to obtain maximal uniformity in road areas. Finally, acquired (off–line) and current (on–line) information are combined to detect road areas in single images.
From quantitative and qualitative experiments, conducted on publicly available datasets, it is concluded that convolutional neural networks are suitable for learning 3D scene layout from noisy labels and provides a relative improvement of 7% compared to the baseline. Furthermore, combining color planes provides a statistical description of road areas that exhibits maximal uniformity and provides a relative improvement of 8% compared to the baseline. Finally, the improvement is even bigger when acquired and current information from a single image are combined
Address Florence, Italy
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-33785-7 Medium
Area Expedition Conference ECCV
Notes ADAS;ISE Approved no
Call Number Admin @ si @ AGL2012; ADAS @ adas @ agl2012a Serial 2022
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Author Ivo Everts; Jan van Gemert; Theo Gevers
Title Per-patch Descriptor Selection using Surface and Scene Properties Type Conference Article
Year 2012 Publication 12th European Conference on Computer Vision Abbreviated Journal
Volume 7577 Issue VI Pages 172-186
Keywords
Abstract Local image descriptors are generally designed for describing all possible image patches. Such patches may be subject to complex variations in appearance due to incidental object, scene and recording conditions. Because of this, a single-best descriptor for accurate image representation under all conditions does not exist. Therefore, we propose to automatically select from a pool of descriptors the one that is best suitable based on object surface and scene properties. These properties are measured on the fly from a single image patch through a set of attributes. Attributes are input to a classifier which selects the best descriptor. Our experiments on a large dataset of colored object patches show that the proposed selection method outperforms the best single descriptor and a-priori combinations of the descriptor pool.
Address Florence, Italy
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-33782-6 Medium
Area Expedition Conference ECCV
Notes ALTRES;ISE Approved no
Call Number Admin @ si @ EGG2012 Serial 2023
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Author Hamdi Dibeklioglu; Theo Gevers; Albert Ali Salah
Title Are You Really Smiling at Me? Spontaneous versus Posed Enjoyment Smiles Type Conference Article
Year 2012 Publication 12th European Conference on Computer Vision Abbreviated Journal
Volume 7574 Issue III Pages 525-538
Keywords
Abstract Smiling is an indispensable element of nonverbal social interaction. Besides, automatic distinction between spontaneous and posed expressions is important for visual analysis of social signals. Therefore, in this paper, we propose a method to distinguish between spontaneous and posed enjoyment smiles by using the dynamics of eyelid, cheek, and lip corner movements. The discriminative power of these movements, and the effect of different fusion levels are investigated on multiple databases. Our results improve the state-of-the-art. We also introduce the largest spontaneous/posed enjoyment smile database collected to date, and report new empirical and conceptual findings on smile dynamics. The collected database consists of 1240 samples of 400 subjects. Moreover, it has the unique property of having an age range from 8 to 76 years. Large scale experiments on the new database indicate that eyelid dynamics are highly relevant for smile classification, and there are age-related differences in smile dynamics.
Address Florence, Italy
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-33711-6 Medium
Area Expedition Conference ECCV
Notes ALTRES;ISE Approved no
Call Number Admin @ si @ DGS2012 Serial 2024
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Author Simeon Petkov; Adriana Romero; Xavier Carrillo; Petia Radeva; Carlo Gatta
Title Robust and accurate diaphragm border detection in cardiac X-Ray angiographies Type Conference Article
Year 2012 Publication Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges Abbreviated Journal
Volume 7746 Issue Pages 225-234
Keywords
Abstract Workshop STACOM, dins del MICCAI
X-ray angiography is the most common imaging modality employed in the diagnosis of coronary diseases prior to or during a catheter-based intervention. The analysis of the patient X-Ray sequence can provide useful information about the degree of arterial stenosis, the myocardial perfusion and other clinical parameters. If the sequence has been acquired to evaluate the perfusion grade, the opacity due to the diaphragm could potentially hinder any kind of visual inspection and make more difficult a computer aided measurements. In this paper we propose an accurate and robust method to automatically identify the diaphragm border in each frame. Quantitative evaluation on a set of 11 sequences shows that the proposed algorithm outperforms previous methods.
Address Nice, France
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-36960-5 Medium
Area Expedition Conference STACOM
Notes MILAB Approved no
Call Number Admin @ si @ PRC2012 Serial 2028
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Author Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
Title Efficient pairwise classification using Local Cross Off strategy Type Conference Article
Year 2012 Publication 25th Canadian Conference on Artificial Intelligence Abbreviated Journal
Volume 7310 Issue Pages 25-36
Keywords
Abstract The pairwise classification approach tends to perform better than other well-known approaches when dealing with multiclass classification problems. In the pairwise approach, however, the nuisance votes of many irrelevant classifiers may result in a wrong prediction class. To overcome this problem, a novel method, Local Crossing Off (LCO), is presented and evaluated in this paper. The proposed LCO system takes advantage of nearest neighbor classification algorithm because of its simplicity and speed, as well as the strength of other two powerful binary classifiers to discriminate between two classes. This paper provides a set of experimental results on 20 datasets using two base learners: Neural Networks and Support Vector Machines. The results show that the proposed technique not only achieves better classification accuracy, but also is computationally more efficient for tackling classification problems which have a relatively large number of target classes.
Address Toronto, Ontario
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-30352-4 Medium
Area Expedition Conference AI
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ BGE2012c Serial 2044
Permanent link to this record