Home [51–60] << 61 62 63 64 65 66 67 68 69 70 >> [71–80]
List View
 | 
Citations
 | 
Details
   web
Records
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 (down) 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 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
Permanent link to this record
 
 
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 (down) 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
Permanent link to this record
 
 
Author Michal Drozdzal; Santiago Segui; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria
Title Motility bar: a new tool for motility analysis of endoluminal videos Type Journal Article
Year 2015 Publication Computers in Biology and Medicine Abbreviated Journal CBM
Volume 65 Issue Pages (down) 320-330
Keywords Small intestine; Motility; WCE; Computer vision; Image classification
Abstract Wireless Capsule Endoscopy (WCE) provides a new perspective of the small intestine, since it enables, for the first time, visualization of the entire organ. However, the long visual video analysis time, due to the large number of data in a single WCE study, was an important factor impeding the widespread use of the capsule as a tool for intestinal abnormalities detection. Therefore, the introduction of WCE triggered a new field for the application of computational methods, and in particular, of computer vision. In this paper, we follow the computational approach and come up with a new perspective on the small intestine motility problem. Our approach consists of three steps: first, we review a tool for the visualization of the motility information contained in WCE video; second, we propose algorithms for the characterization of two motility building-blocks: contraction detector and lumen size estimation; finally, we introduce an approach to detect segments of stable motility behavior. Our claims are supported by an evaluation performed with 10 WCE videos, suggesting that our methods ably capture the intestinal motility information.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MILAB;MV Approved no
Call Number Admin @ si @ DSR2015 Serial 2635
Permanent link to this record
 
 
Author Marta Teres; Eduard Vazquez
Title Museums, spaces and museographical resources. Current state and proposals for a multidisciplinary framework to open new perspectives Type Conference Article
Year 2010 Publication Proceedings of The CREATE 2010 Conference Abbreviated Journal
Volume Issue Pages (down) 319–323
Keywords
Abstract Two of the main aims of a museum are to communicate its heritage and to make enjoy its visitors. This communication can be done through the pieces itself and the museographical resources but also through the building, the interior design, the light and the colour. Art museums, in opposition with other museums, lack on the application of these additional resources. Such a work necessarily requires a multidisciplinary point of view for a holistic vision of all what a museum implies and to use all its potential as a tool of knowledge and culture for all the visitors.
Address Gjovik, Norway
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CREATE
Notes Approved no
Call Number Admin @ si @ TeV2010 Serial 1298
Permanent link to this record
 
 
Author Ivet Rafegas; Maria Vanrell; Luis A Alexandre; G. Arias
Title Understanding trained CNNs by indexing neuron selectivity Type Journal Article
Year 2020 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 136 Issue Pages (down) 318-325
Keywords
Abstract The impressive performance of Convolutional Neural Networks (CNNs) when solving different vision problems is shadowed by their black-box nature and our consequent lack of understanding of the representations they build and how these representations are organized. To help understanding these issues, we propose to describe the activity of individual neurons by their Neuron Feature visualization and quantify their inherent selectivity with two specific properties. We explore selectivity indexes for: an image feature (color); and an image label (class membership). Our contribution is a framework to seek or classify neurons by indexing on these selectivity properties. It helps to find color selective neurons, such as a red-mushroom neuron in layer Conv4 or class selective neurons such as dog-face neurons in layer Conv5 in VGG-M, and establishes a methodology to derive other selectivity properties. Indexing on neuron selectivity can statistically draw how features and classes are represented through layers in a moment when the size of trained nets is growing and automatic tools to index neurons can be helpful.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes CIC; 600.087; 600.140; 600.118 Approved no
Call Number Admin @ si @ RVL2019 Serial 3310
Permanent link to this record
 
 
Author Kaida Xiao; Sophie Wuerger; Chenyang Fu; Dimosthenis Karatzas
Title Unique Hue Data for Colour Appearance Models. Part i: Loci of Unique Hues and Hue Uniformity Type Journal Article
Year 2011 Publication Color Research & Application Abbreviated Journal CRA
Volume 36 Issue 5 Pages (down) 316-323
Keywords unique hues; colour appearance models; CIECAM02; hue uniformity
Abstract Psychophysical experiments were conducted to assess unique hues on a CRT display for a large sample of colour-normal observers (n 1⁄4 185). These data were then used to evaluate the most commonly used colour appear- ance model, CIECAM02, by transforming the CIEXYZ tris- timulus values of the unique hues to the CIECAM02 colour appearance attributes, lightness, chroma and hue angle. We report two findings: (1) the hue angles derived from our unique hue data are inconsistent with the commonly used Natural Color System hues that are incorporated in the CIECAM02 model. We argue that our predicted unique hue angles (derived from our large dataset) provide a more reliable standard for colour management applications when the precise specification of these salient colours is im- portant. (2) We test hue uniformity for CIECAM02 in all four unique hues and show significant disagreements for all hues, except for unique red which seems to be invariant under lightness changes. Our dataset is useful to improve the CIECAM02 model as it provides reliable data for benchmarking.
Address
Corporate Author Thesis
Publisher Wiley Periodicals Inc 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 DAG Approved no
Call Number Admin @ si @ XWF2011 Serial 1816
Permanent link to this record
 
 
Author Yagmur Gucluturk; Umut Guclu; Xavier Baro; Hugo Jair Escalante; Isabelle Guyon; Sergio Escalera; Marcel A. J. van Gerven; Rob van Lier
Title Multimodal First Impression Analysis with Deep Residual Networks Type Journal Article
Year 2018 Publication IEEE Transactions on Affective Computing Abbreviated Journal TAC
Volume 8 Issue 3 Pages (down) 316-329
Keywords
Abstract People form first impressions about the personalities of unfamiliar individuals even after very brief interactions with them. In this study we present and evaluate several models that mimic this automatic social behavior. Specifically, we present several models trained on a large dataset of short YouTube video blog posts for predicting apparent Big Five personality traits of people and whether they seem suitable to be recommended to a job interview. Along with presenting our audiovisual approach and results that won the third place in the ChaLearn First Impressions Challenge, we investigate modeling in different modalities including audio only, visual only, language only, audiovisual, and combination of audiovisual and language. Our results demonstrate that the best performance could be obtained using a fusion of all data modalities. Finally, in order to promote explainability in machine learning and to provide an example for the upcoming ChaLearn challenges, we present a simple approach for explaining the predictions for job interview recommendations
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes HUPBA; no proj Approved no
Call Number Admin @ si @ GGB2018 Serial 3210
Permanent link to this record
 
 
Author Carme Julia; Angel Sappa; Felipe Lumbreras; Antonio Lopez
Title Recovery of Surface Normals and Reflectance from Different Lighting Conditions Type Conference Article
Year 2008 Publication 5th International Conference on Image Analysis and Recognition Abbreviated Journal
Volume 5112 Issue Pages (down) 315–325
Keywords
Abstract
Address
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 ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ JSL2008c Serial 1014
Permanent link to this record
 
 
Author Partha Pratim Roy; Umapada Pal; Josep Llados
Title Multi-oriented English Text Line Extraction using Background and Foreground Information Type Conference Article
Year 2008 Publication Proceedings of the 8th IAPR International Workshop on Document Analysis Systems, Abbreviated Journal
Volume Issue Pages (down) 315–322
Keywords
Abstract
Address Nara (Japo)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference DAS
Notes DAG Approved no
Call Number DAG @ dag @ RPL2008b Serial 1047
Permanent link to this record
 
 
Author Francisco Cruz; Oriol Ramos Terrades
Title EM-Based Layout Analysis Method for Structured Documents Type Conference Article
Year 2014 Publication 22nd International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages (down) 315-320
Keywords
Abstract In this paper we present a method to perform layout analysis in structured documents. We proposed an EM-based algorithm to fit a set of Gaussian mixtures to the different regions according to the logical distribution along the page. After the convergence, we estimate the final shape of the regions according
to the parameters computed for each component of the mixture. We evaluated our method in the task of record detection in a collection of historical structured documents and performed a comparison with other previous works in this task.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1051-4651 ISBN Medium
Area Expedition Conference ICPR
Notes DAG; 602.006; 600.061; 600.077 Approved no
Call Number Admin @ si @ CrR2014 Serial 2530
Permanent link to this record
 
 
Author Marçal Rusiñol; David Aldavert; Dimosthenis Karatzas; Ricardo Toledo; Josep Llados
Title Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval Type Conference Article
Year 2011 Publication 33rd European Conference on Information Retrieval Abbreviated Journal
Volume 6611 Issue Pages (down) 314-325
Keywords
Abstract In this paper we propose an efficient queried-by-example retrieval system which is able to retrieve trademark images by similarity from patent and trademark offices' digital libraries. Logo images are described by both their semantic content, by means of the Vienna codes, and their visual contents, by using shape and color as visual cues. The trademark descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The resulting ranked lists are combined by using the Condorcet method and a relevance feedback step helps to iteratively revise the query and refine the obtained results. The experiments demonstrate the effectiveness and efficiency of this system on a realistic and large dataset.
Address Dublin, Ireland
Corporate Author Thesis
Publisher Springer Place of Publication Berlin Editor P. Clough; C. Foley; C. Gurrin; G.J.F. Jones; W. Kraaij; H. Lee; V. Murdoch
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-20160-8 Medium
Area Expedition Conference ECIR
Notes DAG; RV;ADAS Approved no
Call Number Admin @ si @ RAK2011 Serial 1737
Permanent link to this record
 
 
Author Volkmar Frinken; Andreas Fischer; Horst Bunke; Alicia Fornes
Title Co-training for Handwritten Word Recognition Type Conference Article
Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages (down) 314-318
Keywords
Abstract To cope with the tremendous variations of writing styles encountered between different individuals, unconstrained automatic handwriting recognition systems need to be trained on large sets of labeled data. Traditionally, the training data has to be labeled manually, which is a laborious and costly process. Semi-supervised learning techniques offer methods to utilize unlabeled data, which can be obtained cheaply in large amounts in order, to reduce the need for labeled data. In this paper, we propose the use of Co-Training for improving the recognition accuracy of two weakly trained handwriting recognition systems. The first one is based on Recurrent Neural Networks while the second one is based on Hidden Markov Models. On the IAM off-line handwriting database we demonstrate a significant increase of the recognition accuracy can be achieved with Co-Training for single word recognition.
Address Beijing, China
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ICDAR
Notes DAG Approved no
Call Number Admin @ si @ FFB2011 Serial 1789
Permanent link to this record
 
 
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 (down) 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 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
Permanent link to this record
 
 
Author Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias; A. Moreira
Title Incremental Scenario Representations for Autonomous Driving using Geometric Polygonal Primitives Type Journal Article
Year 2016 Publication Robotics and Autonomous Systems Abbreviated Journal RAS
Volume 83 Issue Pages (down) 312-325
Keywords Incremental scene reconstruction; Point clouds; Autonomous vehicles; Polygonal primitives
Abstract When an autonomous vehicle is traveling through some scenario it receives a continuous stream of sensor data. This sensor data arrives in an asynchronous fashion and often contains overlapping or redundant information. Thus, it is not trivial how a representation of the environment observed by the vehicle can be created and updated over time. This paper presents a novel methodology to compute an incremental 3D representation of a scenario from 3D range measurements. We propose to use macro scale polygonal primitives to model the scenario. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Furthermore, we propose mechanisms designed to update the geometric polygonal primitives over time whenever fresh sensor data is collected. Results show that the approach is capable of producing accurate descriptions of the scene, and that it is computationally very efficient when compared to other reconstruction techniques.
Address
Corporate Author Thesis
Publisher Elsevier B.V. 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; 600.086, 600.076 Approved no
Call Number Admin @ si @OSS2016a Serial 2806
Permanent link to this record
 
 
Author C. Gratin; Jordi Vitria; F. Moreso; D. Seron
Title Texture Classification using Neural Networks and Local Granulometries Type Conference Article
Year 1994 Publication EURASIP Workshop, Mathematical Morphology and Its Applications to image Processing, J.Serra and P.Soille, editors Abbreviated Journal
Volume Issue Pages (down) 309-316
Keywords Neural Networks; Granulometry; Kidney; Texture; Classication
Abstract
Address Fointanebleau, France
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ GVM1994 Serial 110
Permanent link to this record