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Author Laura Igual; Joan Carles Soliva; Roger Gimeno; Sergio Escalera; Oscar Vilarroya; Petia Radeva
Title Automatic Internal Segmentation of Caudate Nucleus for Diagnosis of Attention Deficit Hyperactivity Disorder Type Conference Article
Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal
Volume 7325 Issue II Pages 222-229
Keywords
Abstract Poster
Studies on volumetric brain Magnetic Resonance Imaging (MRI) showed neuroanatomical abnormalities in pediatric Attention-Deficit/Hyperactivity Disorder (ADHD). In particular, the diminished right caudate volume is one of the most replicated findings among ADHD samples in morphometric MRI studies. In this paper, we propose a fully-automatic method for internal caudate nucleus segmentation based on machine learning. Moreover, the ratio between right caudate body volume and the bilateral caudate body volume is applied in a ADHD diagnostic test. We separately validate the automatic internal segmentation of caudate in head and body structures and the diagnostic test using real data from ADHD and control subjects. As a result, we show accurate internal caudate segmentation and similar performance among the proposed automatic diagnostic test and the manual annotation.
Address Aveiro, Portugal
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-31297-7 Medium
Area Expedition Conference ICIAR
Notes OR; HuPBA; MILAB Approved no
Call Number Admin @ si @ ISG2012 Serial 2059
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Author Ricard Borras; Agata Lapedriza; Laura Igual
Title Depth Information in Human Gait Analysis: An Experimental Study on Gender Recognition Type Conference Article
Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal
Volume 7325 Issue II Pages 98-105
Keywords
Abstract This work presents DGait, a new gait database acquired with a depth camera. This database contains videos from 53 subjects walking in different directions. The intent of this database is to provide a public set to explore whether the depth can be used as an additional information source for gait classification purposes. Each video is labelled according to subject, gender and age. Furthermore, for each subject and view point, we provide initial and final frames of an entire walk cycle. On the other hand, we perform gait-based gender classification experiments with DGait database, in order to illustrate the usefulness of depth information for this purpose. In our experiments, we extract 2D and 3D gait features based on shape descriptors, and compare the performance of these features for gender identification, using a Kernel SVM. The obtained results show that depth can be an information source of great relevance for gait classification problems.
Address Aveiro, Portugal
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-31297-7 Medium
Area Expedition Conference ICIAR
Notes OR; MILAB;MV Approved no
Call Number Admin @ si @ BLI2012 Serial 2009
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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 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 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 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 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 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 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 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
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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 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 Bogdan Raducanu; Fadi Dornaika
Title A Discriminative Non-Linear Manifold Learning Technique for Face Recognition Type Book Chapter
Year 2011 Publication Informatics Engineering and Information Science Abbreviated Journal
Volume 254 Issue 6 Pages 339-353
Keywords
Abstract In this paper we propose a novel non-linear discriminative analysis technique for manifold learning. The proposed approach is a discriminant version of Laplacian Eigenmaps which takes into account the class label information in order to guide the procedure of non-linear dimensionality reduction. By following the large margin concept, the graph Laplacian is split in two components: within-class graph and between-class graph to better characterize the discriminant property of the data.
Our approach has been tested on several challenging face databases and it has been conveniently compared with other linear and non-linear techniques. The experimental results confirm that our method outperforms, in general, the existing ones. Although we have concentrated in this paper on the face recognition problem, the proposed approach could also be applied to other category of objects characterized by large variance in their appearance.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1865-0929 ISBN 978-3-642-25482-6 Medium
Area Expedition Conference ICIEIS
Notes OR;MV Approved no
Call Number Admin @ si @ RaD2011 Serial 1804
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Author Angel Sappa; David Geronimo; Fadi Dornaika; Mohammad Rouhani; Antonio Lopez
Title Moving object detection from mobile platforms using stereo data registration Type Book Chapter
Year 2012 Publication Computational Intelligence paradigms in advanced pattern classification Abbreviated Journal
Volume 386 Issue Pages 25-37
Keywords pedestrian detection
Abstract This chapter describes a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three main stages. Initially, feature points are extracted and tracked through consecutive 2D frames. Then, a RANSAC based approach is used for registering two point sets, with known correspondences in the 3D space. The computed 3D rigid displacement is used to map two consecutive 3D point clouds into the same coordinate system by means of the quaternion method. Finally, moving objects correspond to those areas with large 3D registration errors. Experimental results show the viability of the proposed approach to detect moving objects like vehicles or pedestrians in different urban scenarios.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor Marek R. Ogiela; Lakhmi C. Jain
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1860-949X ISBN 978-3-642-24048-5 Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ SGD2012 Serial 2061
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Author Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez
Title Trajectory-Based Abnormality Categorization for Learning Route Patterns in Surveillance Type Book Chapter
Year 2012 Publication Detection and Identification of Rare Audiovisual Cues, Studies in Computational Intelligence Abbreviated Journal
Volume 384 Issue 3 Pages 87-95
Keywords
Abstract The recognition of abnormal behaviors in video sequences has raised as a hot topic in video understanding research. Particularly, an important challenge resides on automatically detecting abnormality. However, there is no convention about the types of anomalies that training data should derive. In surveillance, these are typically detected when new observations differ substantially from observed, previously learned behavior models, which represent normality. This paper focuses on properly defining anomalies within trajectory analysis: we propose a hierarchical representation conformed by Soft, Intermediate, and Hard Anomaly, which are identified from the extent and nature of deviation from learned models. Towards this end, a novel Gaussian Mixture Model representation of learned route patterns creates a probabilistic map of the image plane, which is applied to detect and classify anomalies in real-time. Our method overcomes limitations of similar existing approaches, and performs correctly even when the tracking is affected by different sources of noise. The reliability of our approach is demonstrated experimentally.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1860-949X ISBN 978-3-642-24033-1 Medium
Area Expedition Conference
Notes ISE Approved no
Call Number Admin @ si @ BFR2012 Serial 2062
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Author Muhammad Anwer Rao; David Vazquez; Antonio Lopez
Title Color Contribution to Part-Based Person Detection in Different Types of Scenarios Type Conference Article
Year 2011 Publication 14th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal
Volume 6855 Issue II Pages 463-470
Keywords Pedestrian Detection; Color
Abstract Camera-based person detection is of paramount interest due to its potential applications. The task is diffcult because the great variety of backgrounds (scenarios, illumination) in which persons are present, as well as their intra-class variability (pose, clothe, occlusion). In fact, the class person is one of the included in the popular PASCAL visual object classes (VOC) challenge. A breakthrough for this challenge, regarding person detection, is due to Felzenszwalb et al. These authors proposed a part-based detector that relies on histograms of oriented gradients (HOG) and latent support vector machines (LatSVM) to learn a model of the whole human body and its constitutive parts, as well as their relative position. Since the approach of Felzenszwalb et al. appeared new variants have been proposed, usually giving rise to more complex models. In this paper, we focus on an issue that has not attracted suficient interest up to now. In particular, we refer to the fact that HOG is usually computed from RGB color space, but other possibilities exist and deserve the corresponding investigation. In this paper we challenge RGB space with the opponent color space (OPP), which is inspired in the human vision system.We will compute the HOG on top of OPP, then we train and test the part-based human classifer by Felzenszwalb et al. using PASCAL VOC challenge protocols and person database. Our experiments demonstrate that OPP outperforms RGB. We also investigate possible differences among types of scenarios: indoor, urban and countryside. Interestingly, our experiments suggest that the beneficts of OPP with respect to RGB mainly come for indoor and countryside scenarios, those in which the human visual system was designed by evolution.
Address Seville, Spain
Corporate Author Thesis
Publisher Springer Place of Publication Berlin Heidelberg Editor P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch
Language English Summary Language english Original Title Color Contribution to Part-Based Person Detection in Different Types of Scenarios
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-23677-8 Medium
Area Expedition Conference CAIP
Notes ADAS Approved no
Call Number ADAS @ adas @ RVL2011b Serial 1665
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Author Naveen Onkarappa; Angel Sappa
Title Space Variant Representations for Mobile Platform Vision Applications Type Conference Article
Year 2011 Publication 14th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal
Volume 6855 Issue II Pages 146-154
Keywords
Abstract The log-polar space variant representation, motivated by biological vision, has been widely studied in the literature. Its data reduction and invariance properties made it useful in many vision applications. However, due to its nature, it fails in preserving features in the periphery. In the current work, as an attempt to overcome this problem, we propose a novel space-variant representation. It is evaluated and proved to be better than the log-polar representation in preserving the peripheral information, crucial for on-board mobile vision applications. The evaluation is performed by comparing log-polar and the proposed representation once they are used for estimating dense optical flow.
Address Seville, Spain
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-23677-8 Medium
Area Expedition Conference CAIP
Notes ADAS Approved no
Call Number NaS2011; ADAS @ adas @ Serial 1686
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Author Francesco Ciompi; Oriol Pujol; Carlo Gatta; Xavier Carrillo; Josepa Mauri; Petia Radeva
Title A Holistic Approach for the Detection of Media-Adventitia Border in IVUS Type Conference Article
Year 2011 Publication 14th International Conference on Medical Image Computing and Computer Assisted Intervention Abbreviated Journal
Volume 6893 Issue Pages 401-408
Keywords
Abstract In this paper we present a methodology for the automatic detection of media-adventitia border (MAb) in Intravascular Ultrasound. A robust computation of the MAb is achieved through a holistic approach where the position of the MAb with respect to other tissues of the vessel is used. A learned quality measure assures that the resulting MAb is optimal with respect to all other tissues. The mean distance error computed through a set of 140 images is 0.2164 (±0.1326) mm.
Address Toronto, Canada
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-23625-9 Medium
Area Expedition Conference MICCAI
Notes MILAB;HuPBA Approved no
Call Number Admin @ si @ CPG2011 Serial 1739
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Author Xavier Perez Sala; Cecilio Angulo; Sergio Escalera
Title Biologically Inspired Path Execution Using SURF Flow in Robot Navigation Type Conference Article
Year 2011 Publication 11th International Work Conference on Artificial Neural Networks Abbreviated Journal
Volume II Issue Pages 581--588
Keywords
Abstract An exportable and robust system using only camera images is proposed for path execution in robot navigation. Motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames, so the method is called SURF flow. This information is used to correct robot displacement when a straight forward path command is sent to the robot, but it is not really executed due to several robot and environmental concerns. The proposed system has been successfully tested on the legged robot Aibo.
Address Malaga
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-21497-4 Medium
Area Expedition Conference IWANN
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ PAE2011b Serial 1773
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Author Farhan Riaz; Fernando Vilariño; Mario Dinis-Ribeiro; Miguel Coimbraln
Title Identifying Potentially Cancerous Tissues in Chromoendoscopy Images Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 709-716
Keywords Endoscopy, Computer Assisted Diagnosis, Gradient.
Abstract The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered.
Address Las Palmas de Gran Canaria. Spain
Corporate Author Thesis
Publisher Springer Place of Publication Berlin Editor J. Vitria, J.M. Sanches, and M. Hernandez
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-21256-7 Medium
Area 800 Expedition Conference IbPRIA
Notes MV;SIAI Approved no
Call Number Admin @ si @ RVD2011; IAM @ iam @ RVD2011 Serial 1726
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