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Author Joost Van de Weijer; Robert Benavente; Maria Vanrell; Cordelia Schmid; Ramon Baldrich; Jacob Verbeek; Diane Larlus
Title Color Naming Type Book Chapter
Year 2012 Publication Color in Computer Vision: Fundamentals and Applications Abbreviated Journal
Volume Issue 17 Pages 287-317
Keywords
Abstract
Address
Corporate Author Thesis
Publisher (down) John Wiley & Sons, Ltd. Place of Publication Editor Theo Gevers;Arjan Gijsenij;Joost Van de Weijer;Jan-Mark Geusebroek
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes CIC Approved no
Call Number Admin @ si @ WBV2012 Serial 2063
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Author Antonio Lopez; Atsushi Imiya; Tomas Pajdla; Jose Manuel Alvarez
Title Computer Vision in Vehicle Technology: Land, Sea & Air Type Book Whole
Year 2017 Publication Abbreviated Journal
Volume Issue Pages 161-163
Keywords
Abstract Summary This chapter examines different vision-based commercial solutions for real-live problems related to vehicles. It is worth mentioning the recent astonishing performance of deep convolutional neural networks (DCNNs) in difficult visual tasks such as image classification, object recognition/localization/detection, and semantic segmentation. In fact,
different DCNN architectures are already being explored for low-level tasks such as optical flow and disparity computation, and higher level ones such as place recognition.
Address
Corporate Author Thesis
Publisher (down) 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 978-1-118-86807-2 Medium
Area Expedition Conference
Notes ADAS; 600.118 Approved no
Call Number Admin @ si @ LIP2017a Serial 2937
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Author David Aldavert; Arnau Ramisa; Ramon Lopez de Mantaras; Ricardo Toledo
Title Real-time Object Segmentation using a Bag of Features Approach Type Conference Article
Year 2010 Publication 13th International Conference of the Catalan Association for Artificial Intelligence Abbreviated Journal
Volume 220 Issue Pages 321–329
Keywords Object Segmentation; Bag Of Features; Feature Quantization; Densely sampled descriptors
Abstract In this paper, we propose an object segmentation framework, based on the popular bag of features (BoF), which can process several images per second while achieving a good segmentation accuracy assigning an object category to every pixel of the image. We propose an efficient color descriptor to complement the information obtained by a typical gradient-based local descriptor. Results show that color proves to be a useful cue to increase the segmentation accuracy, specially in large homogeneous regions. Then, we extend the Hierarchical K-Means codebook using the recently proposed Vector of Locally Aggregated Descriptors method. Finally, we show that the BoF method can be easily parallelized since it is applied locally, thus the time necessary to process an image is further reduced. The performance of the proposed method is evaluated in the standard PASCAL 2007 Segmentation Challenge object segmentation dataset.
Address
Corporate Author Thesis
Publisher (down) IOS Press Amsterdam, Place of Publication Editor In R.Alquezar, A.Moreno, J.Aguilar.
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 9781607506423 Medium
Area Expedition Conference CCIA
Notes ADAS Approved no
Call Number Admin @ si @ ARL2010b Serial 1417
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Author Fernando Vilariño; Petia Radeva
Title Cardiac Segmentation with Discriminant Active Contours Type Book Chapter
Year 2003 Publication Abbreviated Journal
Volume Issue Pages 211–217
Keywords
Abstract Dynamic tracking of heart moving is one relevant target in medical imag- ing and can be helpful for analyzing heart dynamics in the study of several cardiac diseases. For this aim, a previous segmentation problem of such structures is stated, based on certain relevant features (like edges or intensity levels, textures, etc.) Clas- sical active models have been used, but they fail when overlapping structures or not well-defined contours are present. Automatic feature learning systems may be a pow- erful tool. Discriminant active contours present optimal results in this kind of problem. They are a kind of deformable models that converge to an optimal object segmenta- tion that dynamically adapts to the object contour. The feature space is designed from a filter bank in order to guarantee the search and learning of the set of relevant fea- tures for optimal classification on each part of the object. Tracking of target evolution is obtained through the whole set of images, using information from the actual and previous stages. Feedback systems are implemented to guarantee the minimum well- separable classification set in each segmentation step. Our implementation has been proved with several series of Magnetic Resonance with improved results in segmenta- tion in comparison to previous methods.
Address Palma de Mallorca
Corporate Author Thesis
Publisher (down) IOS Press Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CCIA
Notes MV;MILAB;SIAI Approved no
Call Number BCNPCL @ bcnpcl @ ViR2003; IAM @ iam @ VRa2003 Serial 426
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Author Joel Barajas; Jaume Garcia; Francesc Carreras; Sandra Pujades; Petia Radeva
Title Angle Images Using Gabor Filters in Cardiac Tagged MRI Type Conference Article
Year 2005 Publication Proceeding of the 2005 conference on Artificial Intelligence Research and Development Abbreviated Journal
Volume Issue Pages 107-114
Keywords Angle Images, Gabor Filters, Harp, Tagged Mri
Abstract Tagged Magnetic Resonance Imaging (MRI) is a non-invasive technique used to examine cardiac deformation in vivo. An Angle Image is a representation of a Tagged MRI which recovers the relative position of the tissue respect to the distorted tags. Thus cardiac deformation can be estimated. This paper describes a new approach to generate Angle Images using a bank of Gabor filters in short axis cardiac Tagged MRI. Our method improves the Angle Images obtained by global techniques, like HARP, with a local frequency analysis. We propose to use the phase response of a combination of a Gabor filters bank, and use it to find a more precise deformation of the left ventricle. We demonstrate the accuracy of our method over HARP by several experimental results.
Address Amsterdam; The Netherlands
Corporate Author Thesis
Publisher (down) IOS Press Place of Publication Amsterdam, The Netherlands Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 1-58603-560-6 Medium
Area Expedition Conference CAIRD
Notes IAM;MILAB Approved no
Call Number BCNPCL @ bcnpcl @ BGC2005; IAM @ iam Serial 595
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Author Antonio Lopez; W. Niessen; Joan Serrat; K. Nikolay; B. Ter Haar Romeny; Juan J. Villanueva; M. Viergerver
Title New improvements in the multiscale analysis of trabecular bone patterns Type Book Chapter
Year 2000 Publication Pattern Recognition and Applications Abbreviated Journal
Volume Issue Pages 251-260
Keywords
Abstract
Address
Corporate Author Thesis
Publisher (down) IOS Press Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ Serial 3418
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Author Jaume Garcia; Petia Radeva; Francesc Carreras
Title Combining Spectral and Active Shape methods to Track Tagged MRI Type Book Chapter
Year 2004 Publication Recent Advances in Artificial Intelligence Research and Development Abbreviated Journal
Volume Issue Pages 37-44
Keywords MR; tagged MR; ASM; LV segmentation; motion estimation.
Abstract Tagged magnetic resonance is a very usefull and unique tool that provides a complete local and global knowledge of the left ventricle (LV) motion. In this article we introduce a method capable of tracking and segmenting the LV. Spectral methods are applied in order to obtain the so called HARP images which encode information about movement and are the base for LV point-tracking. For segmentation we use Active Shapes (ASM) that model LV shape variation in order to overcome possible local misplacements of the boundary. We finally show experiments on both synthetic and real data which appear to be very promising.
Address
Corporate Author Thesis
Publisher (down) IOS Press Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CCIA
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GRC2004 Serial 1488
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Author Debora Gil; Petia Radeva
Title Inhibition of False Landmarks Type Book Chapter
Year 2004 Publication Recent Advances in Artificial Intelligence Research and Development Abbreviated Journal
Volume Issue Pages 233-244
Keywords
Abstract We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Its high sensitivity to changes in vector directions makes it suitable for landmark location in real images prone to need smoothing to reduce the impact of noise. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our Inhibition Orientation Energy (IOE) landmark locator.
Address
Corporate Author Thesis
Publisher (down) IOS Press Place of Publication Barcelona (Spain) Editor al, J.V. et
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GiR2004a Serial 1533
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Author Aura Hernandez-Sabate; Debora Gil; Petia Radeva
Title On the usefulness of supervised learning for vessel border detection in IntraVascular Imaging Type Conference Article
Year 2005 Publication Proceeding of the 2005 conference on Artificial Intelligence Research and Development Abbreviated Journal
Volume Issue Pages 67-74
Keywords classification; vessel border modelling; IVUS
Abstract IntraVascular UltraSound (IVUS) imaging is a useful tool in diagnosis of cardiac diseases since sequences completely show the morphology of coronary vessels. Vessel borders detection, especially the external adventitia layer, plays a central role in morphological measures and, thus, their segmentation feeds development of medical imaging techniques. Deterministic approaches fail to yield optimal results due to the large amount of IVUS artifacts and vessel borders descriptors. We propose using classification techniques to learn the set of descriptors and parameters that best detect vessel borders. Statistical hypothesis test on the error between automated detections and manually traced borders by 4 experts show that our detections keep within inter-observer variability.
Address
Corporate Author Thesis
Publisher (down) IOS Press Place of Publication Amsterdam, The Netherlands Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ HGR2005c Serial 1549
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Author Fernando Vilariño; Debora Gil; Petia Radeva
Title A Novel FLDA Formulation for Numerical Stability Analysis Type Book Chapter
Year 2004 Publication Recent Advances in Artificial Intelligence Research and Development Abbreviated Journal
Volume 113 Issue Pages 77-84
Keywords Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision
Abstract Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision.
Address
Corporate Author Thesis
Publisher (down) IOS Press Place of Publication Editor J. Vitrià, P. Radeva and I. Aguiló
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-58603-466-5 Medium
Area Expedition Conference
Notes MV;IAM;MILAB;SIAI Approved no
Call Number IAM @ iam @ VGR2004 Serial 1663
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Author Jordina Torrents-Barrena; Aida Valls; Petia Radeva; Meritxell Arenas; Domenec Puig
Title Automatic Recognition of Molecular Subtypes of Breast Cancer in X-Ray images using Segmentation-based Fractal Texture Analysis Type Book Chapter
Year 2015 Publication Artificial Intelligence Research and Development Abbreviated Journal
Volume 277 Issue Pages 247 - 256
Keywords
Abstract Breast cancer disease has recently been classified into four subtypes regarding the molecular properties of the affected tumor region. For each patient, an accurate diagnosis of the specific type is vital to decide the most appropriate therapy in order to enhance life prospects. Nowadays, advanced therapeutic diagnosis research is focused on gene selection methods, which are not robust enough. Hence, we hypothesize that computer vision algorithms can offer benefits to address the problem of discriminating among them through X-Ray images. In this paper, we propose a novel approach driven by texture feature descriptors and machine learning techniques. First, we segment the tumour part through an active contour technique and then, we perform a complete fractal analysis to collect qualitative information of the region of interest in the feature extraction stage. Finally, several supervised and unsupervised classifiers are used to perform multiclass classification of the aforementioned data. The experimental results presented in this paper support that it is possible to establish a relation between each tumor subtype and the extracted features of the patterns revealed on mammograms.
Address
Corporate Author Thesis
Publisher (down) IOS Press Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Frontiers in Artificial Intelligence and Applications Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number Admin @ si @TVR2015 Serial 2780
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Author Aura Hernandez-Sabate; Debora Gil
Title The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries Type Book Chapter
Year 2012 Publication Intravascular Ultrasound Abbreviated Journal
Volume Issue Pages 185-206
Keywords
Abstract
Address
Corporate Author Thesis
Publisher (down) Intech Place of Publication Editor Yasuhiro Honda
Language English Summary Language english Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-953-307-900-4 Medium
Area Expedition Conference
Notes IAM; ADAS Approved no
Call Number IAM @ iam @ HeG2012 Serial 1684
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Author Jorge Bernal; Fernando Vilariño; F. Javier Sanchez
Title Towards Intelligent Systems for Colonoscopy Type Book Chapter
Year 2011 Publication Colonoscopy Abbreviated Journal
Volume 1 Issue Pages 257-282
Keywords
Abstract In this chapter we present tools that can be used to build intelligent systems for colonoscopy.
The idea is, by using methods based on computer vision and artificial intelligence, add significant value to the colonoscopy procedure. Intelligent systems are being used to assist in other medical interventions
Address
Corporate Author Thesis
Publisher (down) Intech Place of Publication Editor Paul Miskovitz
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-953-307-568-6 Medium
Area 800 Expedition Conference
Notes MV;SIAI Approved no
Call Number IAM @ iam @ BVS2011 Serial 1697
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Author F.X. Perez; F. Javier Sanchez; Xavier Binefa; Xavier Roca; Jordi Vitria; Juan J. Villanueva
Title A mathematical morphology-based system for IC´s inspection and analysis. Type Conference Article
Year 1993 Publication Institute of Physics Conferences Series Abbreviated Journal
Volume 135 Issue 10 Pages 381–384
Keywords
Abstract
Address Bristol
Corporate Author Thesis
Publisher (down) Institute of Physics Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MV;OR;ISE Approved no
Call Number BCNPCL @ bcnpcl @ PSB1993; IAM @ iam @ PSB1993 Serial 150
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Author X. Binefa; F. Javier Sanchez; F.X. Perez; Xavier Roca; Jordi Vitria; Juan J. Villanueva
Title Using defocus in optical inspection of integrated circuits Type Conference Article
Year 1993 Publication Institute of Physics Conferences Series Abbreviated Journal
Volume 135 Issue 10 Pages 389-392
Keywords
Abstract
Address Bristol
Corporate Author Thesis
Publisher (down) Institute of Physics Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MV;OR;ISE Approved no
Call Number BCNPCL @ bcnpcl @ BSP1993; IAM @ iam @ BSP1993 Serial 151
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