| Records |
| Author |
Xialei Liu; Joost Van de Weijer; Andrew Bagdanov |
| Title |
Exploiting Unlabeled Data in CNNs by Self-Supervised Learning to Rank |
Type |
Journal Article |
| Year |
2019 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
| Volume |
41 |
Issue  |
8 |
Pages |
1862-1878 |
| Keywords |
Task analysis;Training;Image quality;Visualization;Uncertainty;Labeling;Neural networks;Learning from rankings;image quality assessment;crowd counting;active learning |
| Abstract |
For many applications the collection of labeled data is expensive laborious. Exploitation of unlabeled data during training is thus a long pursued objective of machine learning. Self-supervised learning addresses this by positing an auxiliary task (different, but related to the supervised task) for which data is abundantly available. In this paper, we show how ranking can be used as a proxy task for some regression problems. As another contribution, we propose an efficient backpropagation technique for Siamese networks which prevents the redundant computation introduced by the multi-branch network architecture. We apply our framework to two regression problems: Image Quality Assessment (IQA) and Crowd Counting. For both we show how to automatically generate ranked image sets from unlabeled data. Our results show that networks trained to regress to the ground truth targets for labeled data and to simultaneously learn to rank unlabeled data obtain significantly better, state-of-the-art results for both IQA and crowd counting. In addition, we show that measuring network uncertainty on the self-supervised proxy task is a good measure of informativeness of unlabeled data. This can be used to drive an algorithm for active learning and we show that this reduces labeling effort by up to 50 percent. |
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LAMP; 600.109; 600.106; 600.120 |
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no |
| Call Number |
LWB2019 |
Serial |
3267 |
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| Author |
Akhil Gurram; Ahmet Faruk Tuna; Fengyi Shen; Onay Urfalioglu; Antonio Lopez |
| Title |
Monocular Depth Estimation through Virtual-world Supervision and Real-world SfM Self-Supervision |
Type |
Journal Article |
| Year |
2021 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
Abbreviated Journal |
TITS |
| Volume |
23 |
Issue |
8 |
Pages |
12738-12751 |
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| Abstract |
Depth information is essential for on-board perception in autonomous driving and driver assistance. Monocular depth estimation (MDE) is very appealing since it allows for appearance and depth being on direct pixelwise correspondence without further calibration. Best MDE models are based on Convolutional Neural Networks (CNNs) trained in a supervised manner, i.e., assuming pixelwise ground truth (GT). Usually, this GT is acquired at training time through a calibrated multi-modal suite of sensors. However, also using only a monocular system at training time is cheaper and more scalable. This is possible by relying on structure-from-motion (SfM) principles to generate self-supervision. Nevertheless, problems of camouflaged objects, visibility changes, static-camera intervals, textureless areas, and scale ambiguity, diminish the usefulness of such self-supervision. In this paper, we perform monocular depth estimation by virtual-world supervision (MonoDEVS) and real-world SfM self-supervision. We compensate the SfM self-supervision limitations by leveraging virtual-world images with accurate semantic and depth supervision and addressing the virtual-to-real domain gap. Our MonoDEVSNet outperforms previous MDE CNNs trained on monocular and even stereo sequences. |
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ADAS; 600.118 |
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no |
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Admin @ si @ GTS2021 |
Serial |
3598 |
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| Author |
Aura Hernandez-Sabate; Lluis Albarracin; F. Javier Sanchez |
| Title |
Graph-Based Problem Explorer: A Software Tool to Support Algorithm Design Learning While Solving the Salesperson Problem |
Type |
Journal |
| Year |
2020 |
Publication |
Mathematics |
Abbreviated Journal |
MATH |
| Volume |
20 |
Issue |
8(9) |
Pages |
1595 |
| Keywords |
STEM education; Project-based learning; Coding; software tool |
| Abstract |
In this article, we present a sequence of activities in the form of a project in order to promote
learning on design and analysis of algorithms. The project is based on the resolution of a real problem, the salesperson problem, and it is theoretically grounded on the fundamentals of mathematical modelling. In order to support the students’ work, a multimedia tool, called Graph-based Problem Explorer (GbPExplorer), has been designed and refined to promote the development of computer literacy in engineering and science university students. This tool incorporates several modules to allow coding different algorithmic techniques solving the salesman problem. Based on an educational design research along five years, we observe that working with GbPExplorer during the project provides students with the possibility of representing the situation to be studied in the form of graphs and analyze them from a computational point of view. |
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September 2020 |
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IAM; ISE |
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no |
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Admin @ si @ |
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3722 |
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| Author |
Aura Hernandez-Sabate |
| Title |
Automatic adventitia segmentation in IntraVascular UltraSound images |
Type |
Report |
| Year |
2005 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
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Issue |
85 |
Pages |
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| Abstract |
A usual tool in cardiac disease diagnosis is vessel plaque assessment by analysis of IVUS sequences. Manual detection of lumen-intima, intima-media and media-adventitia vessel borders is the main activity of physicians in the process of plaque quantification. Large variety in vessel border descriptors, as well as, shades, artifacts and blurred response due to ultrasound physical properties troubles automated media-adventitia segmentation. This experimental work presents a solution to such a complex problem. The process blends advanced anisotropic filtering operators and statistic classification techniques, achieving an efficient vessel border modelling strategy. First of all, we introduce the theoretic base of the method. After that, we show the steps of the algorithm, validating the method with statistics that show that the media-adventitia border detection achieves an accuracy in the range of inter-observer variability regardless of plaque nature, vessel geometry and incomplete vessel borders. Finally, we present a little Matlab application to the automatic media-adventitia border. |
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Thesis |
Master's thesis |
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Place of Publication |
08193 Bellaterra, Barcelona (Spain) |
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IAM; |
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IAM @ iam @ Her2005 |
Serial |
1544 |
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| Author |
Aura Hernandez-Sabate; Debora Gil; Petia Radeva |
| Title |
A Deterministic-Statistical Strategy for Adventitia Segmentation in IVUS images |
Type |
Report |
| Year |
2005 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
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Issue |
89 |
Pages |
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| Abstract |
A useful tool for some specific studies in cardiac disease diagnosis is vessel plaque assessment by analysis of IVUS sequences. Manual detection of luminal (inner) and media-adventitia (external) vessel borders is the main activity of physicians in the process of lumen narrowing (plaque) quantification. Difficult definition of vessel border descriptors, as well as, shades, artifacts and blurred signal response due to ultrasound physical properties troubles automated adventitia segmentation. In order to efficiently approach such a complex problem, we propose blending advanced anisotropic filtering operators and statistical classification techniques into a vessel border modelling strategy. Our systematic statistical analysis shows that the reported adventitia detection achieves an accuracy in the range of inter-observer variability regardless of plaque nature, vessel geometry and incomplete vessel borders. |
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IAM; MILAB |
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no |
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IAM @ iam @ HGR2005a |
Serial |
1548 |
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| Author |
Judit Martinez; F. Thomas |
| Title |
Efficient Computation of Local Geometric Moments |
Type |
Journal Article |
| Year |
2002 |
Publication |
IEEE Transactions on Image Porcessing, (IF: 2.553) |
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| Volume |
11 |
Issue |
9 |
Pages |
1102-1111 |
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no |
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Admin @ si @ MaT2002 |
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271 |
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| Author |
Jose Antonio Rodriguez; Florent Perronnin |
| Title |
Handwritten word-spotting using hidden Markov models and universal vocabularies |
Type |
Journal Article |
| Year |
2009 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
42 |
Issue |
9 |
Pages |
2103-2116 |
| Keywords |
Word-spotting; Hidden Markov model; Score normalization; Universal vocabulary; Handwriting recognition |
| Abstract |
Handwritten word-spotting is traditionally viewed as an image matching task between one or multiple query word-images and a set of candidate word-images in a database. This is a typical instance of the query-by-example paradigm. In this article, we introduce a statistical framework for the word-spotting problem which employs hidden Markov models (HMMs) to model keywords and a Gaussian mixture model (GMM) for score normalization. We explore the use of two types of HMMs for the word modeling part: continuous HMMs (C-HMMs) and semi-continuous HMMs (SC-HMMs), i.e. HMMs with a shared set of Gaussians. We show on a challenging multi-writer corpus that the proposed statistical framework is always superior to a traditional matching system which uses dynamic time warping (DTW) for word-image distance computation. A very important finding is that the SC-HMM is superior when labeled training data is scarce—as low as one sample per keyword—thanks to the prior information which can be incorporated in the shared set of Gaussians. |
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Elsevier |
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0031-3203 |
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no |
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Admin @ si @ RoP2009 |
Serial |
1053 |
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| Author |
Fadi Dornaika; Angel Sappa |
| Title |
A Featureless and Stochastic Approach to On-board Stereo Vision System Pose |
Type |
Journal Article |
| Year |
2009 |
Publication |
Image and Vision Computing |
Abbreviated Journal |
IMAVIS |
| Volume |
27 |
Issue |
9 |
Pages |
1382–1393 |
| Keywords |
On-board stereo vision system; Pose estimation; Featureless approach; Particle filtering; Image warping |
| Abstract |
This paper presents a direct and stochastic technique for real-time estimation of on-board stereo head’s position and orientation. Unlike existing works which rely on feature extraction either in the image domain or in 3D space, our proposed approach directly estimates the unknown parameters from the stream of stereo pairs’ brightness. The pose parameters are tracked using the particle filtering framework which implicitly enforces the smoothness constraints on the estimated parameters. The proposed technique can be used with a driver assistance applications as well as with augmented reality applications. Extended experiments on urban environments with different road geometries are presented. Comparisons with a 3D data-based approach are presented. Moreover, we provide a performance study aiming at evaluating the accuracy of the proposed approach. |
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ADAS |
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no |
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ADAS @ adas @ DoS2009b |
Serial |
1152 |
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| Author |
Miquel Ferrer; Ernest Valveny; F. Serratosa |
| Title |
Median Graphs: A Genetic Approach based on New Theoretical Properties |
Type |
Journal Article |
| Year |
2009 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
42 |
Issue |
9 |
Pages |
2003–2012 |
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Median graph; Genetic search; Maximum common subgraph; Graph matching; Structural pattern recognition |
| Abstract |
Given a set of graphs, the median graph has been theoretically presented as a useful concept to infer a representative of the set. However, the computation of the median graph is a highly complex task and its practical application has been very limited up to now. In this work we present two major contributions. On one side, and from a theoretical point of view, we show new theoretical properties of the median graph. On the other side, using these new properties, we present a new approximate algorithm based on the genetic search, that improves the computation of the median graph. Finally, we perform a set of experiments on real data, where none of the existing algorithms for the median graph computation could be applied up to now due to their computational complexity. With these results, we show how the concept of the median graph can be used in real applications and leaves the box of the only-theoretical concepts, demonstrating, from a practical point of view, that can be a useful tool to represent a set of graphs. |
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DAG |
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no |
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DAG @ dag @ FVS2009b |
Serial |
1167 |
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| Author |
Oriol Ramos Terrades; Ernest Valveny; Salvatore Tabbone |
| Title |
Optimal Classifier Fusion in a Non-Bayesian Probabilistic Framework |
Type |
Journal Article |
| Year |
2009 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
| Volume |
31 |
Issue |
9 |
Pages |
1630–1644 |
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The combination of the output of classifiers has been one of the strategies used to improve classification rates in general purpose classification systems. Some of the most common approaches can be explained using the Bayes' formula. In this paper, we tackle the problem of the combination of classifiers using a non-Bayesian probabilistic framework. This approach permits us to derive two linear combination rules that minimize misclassification rates under some constraints on the distribution of classifiers. In order to show the validity of this approach we have compared it with other popular combination rules from a theoretical viewpoint using a synthetic data set, and experimentally using two standard databases: the MNIST handwritten digit database and the GREC symbol database. Results on the synthetic data set show the validity of the theoretical approach. Indeed, results on real data show that the proposed methods outperform other common combination schemes. |
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0162-8828 |
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DAG |
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no |
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DAG @ dag @ RVT2009 |
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1220 |
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| Author |
David Geronimo; Angel Sappa; Antonio Lopez |
| Title |
Stereo-based Candidate Generation for Pedestrian Protection Systems |
Type |
Book Chapter |
| Year |
2010 |
Publication |
Binocular Vision: Development, Depth Perception and Disorders |
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Issue |
9 |
Pages |
189–208 |
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Pedestrian Detection |
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This chapter describes a stereo-based algorithm that provides candidate image windows to a latter 2D classification stage in an on-board pedestrian detection system. The proposed algorithm, which consists of three stages, is based on the use of both stereo imaging and scene prior knowledge (i.e., pedestrians are on the ground) to reduce the candidate searching space. First, a successful road surface fitting algorithm provides estimates on the relative ground-camera pose. This stage directs the search toward the road area thus avoiding irrelevant regions like the sky. Then, three different schemes are used to scan the estimated road surface with pedestrian-sized windows: (a) uniformly distributed through the road surface (3D); (b) uniformly distributed through the image (2D); (c) not uniformly distributed but according to a quadratic function (combined 2D-3D). Finally, the set of candidate windows is reduced by analyzing their 3D content. Experimental results of the proposed algorithm, together with statistics of searching space reduction are provided. |
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NOVA Publishers |
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ADAS |
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no |
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ADAS @ adas @ GSL2010 |
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1301 |
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| Author |
Debora Gil; Aura Hernandez-Sabate; Mireia Brunat;Steven Jansen; Jordi Martinez-Vilalta |
| Title |
Structure-preserving smoothing of biomedical images |
Type |
Journal Article |
| Year |
2011 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
44 |
Issue |
9 |
Pages |
1842-1851 |
| Keywords |
Non-linear smoothing; Differential geometry; Anatomical structures; segmentation; Cardiac magnetic resonance; Computerized tomography |
| Abstract |
Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images. |
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0031-3203 |
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IAM; ADAS |
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no |
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IAM @ iam @ GHB2011 |
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1526 |
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| Author |
Debora Gil; Petia Radeva |
| Title |
Inhibition of false landmarks |
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Journal Article |
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2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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27 |
Issue |
9 |
Pages |
1022-1030 |
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Corners and junctions are landmarks characterized by the lack of differentiability in the unit tangent to the image level curve. Detectors based on differential operators are not, by their own definition, the best posed as they require a higher degree of differentiability to yield a reliable response. 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. 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. |
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Elsevier Science Inc. |
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New York, NY, USA |
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0167-8655 |
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IAM;MILAB |
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no |
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IAM @ iam @ GiR2006 |
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1529 |
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| Author |
Enric Marti |
| Title |
Análisis de elementos gráficos en documentos |
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Report |
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1996 |
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CVC Technical Report |
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9 |
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En este texto se presenta un estudio sobre las t’ecnicas y aplicaciones de an’alisis de documentos, y más concretamente abordando la problem’atica del an’alisis de de entidades gr’aficas. El ’area de an’alisis de documentos tiene como objetivo la interpretaci’on de documentos impresos sobre papel por m’etodos computacionales, para obtener una descripci’on con un alto nivel de abstracci’on, que permita su posterior tratamiento y archivo por m’etodos inform’aticos. Este objetivo, junto a los trabajos realizados hasta el momento, le otorgan a esta ’area un amplio ’ambito de aplicaciones para la manipulaci’on y archivo de documentos sobre papel, que puede llegar a significar un salto cualitativo importante (del papel al disco ’optico) en el uso de soportes de informaci’on, debido a las importantes prestaciones de acceso y capacidad de archivo que suponen los medios inform’aticos. Generalmente los documentos son introducidos en los sistemas de an’alisis de documentos mediante scanner, obt... |
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Computer Vision Centre |
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CVC UAB |
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IAM; |
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IAM @ iam @ Mar1996 |
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1587 |
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| Author |
Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
| Title |
Computational Color Constancy: Survey and Experiments |
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Journal Article |
| Year |
2011 |
Publication |
IEEE Transactions on Image Processing |
Abbreviated Journal |
TIP |
| Volume |
20 |
Issue |
9 |
Pages |
2475-2489 |
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computational color constancy;computer vision application;gamut-based method;learning-based method;static method;colour vision;computer vision;image colour analysis;learning (artificial intelligence);lighting |
| Abstract |
Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-the- art methods. Several criteria are proposed that are used to assess the approaches. A taxonomy of existing algorithms is proposed and methods are separated in three groups: static methods, gamut-based methods and learning-based methods. Further, the experimental setup is discussed including an overview of publicly available data sets. Finally, various freely available methods, of which some are considered to be state-of-the-art, are evaluated on two data sets. |
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1057-7149 |
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ISE;CIC |
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Admin @ si @ GGW2011 |
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1717 |
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