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| Author | Albert Gordo; Florent Perronnin; Ernest Valveny | ||||
Title  |
Large-scale document image retrieval and classification with runlength histograms and binary embeddings | Type | Journal Article | ||
| Year | 2013 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 46 | Issue | 7 | Pages | 1898-1905 |
| Keywords | visual document descriptor; compression; large-scale; retrieval; classification | ||||
| Abstract | We present a new document image descriptor based on multi-scale runlength
histograms. This descriptor does not rely on layout analysis and can be computed efficiently. We show how this descriptor can achieve state-of-theart results on two very different public datasets in classification and retrieval tasks. Moreover, we show how we can compress and binarize these descriptors to make them suitable for large-scale applications. We can achieve state-ofthe- art results in classification using binary descriptors of as few as 16 to 64 bits. |
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| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0031-3203 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; 600.042; 600.045; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ GPV2013 | Serial | 2306 | ||
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| Author | Bhaskar Chakraborty; Jordi Gonzalez; Xavier Roca | ||||
| Title |
Large scale continuous visual event recognition using max-margin Hough transformation framework | Type | Journal Article | ||
| Year | 2013 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
| Volume | 117 | Issue | 10 | Pages | 1356–1368 |
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| Abstract | In this paper we propose a novel method for continuous visual event recognition (CVER) on a large scale video dataset using max-margin Hough transformation framework. Due to high scalability, diverse real environmental state and wide scene variability direct application of action recognition/detection methods such as spatio-temporal interest point (STIP)-local feature based technique, on the whole dataset is practically infeasible. To address this problem, we apply a motion region extraction technique which is based on motion segmentation and region clustering to identify possible candidate “event of interest” as a preprocessing step. On these candidate regions a STIP detector is applied and local motion features are computed. For activity representation we use generalized Hough transform framework where each feature point casts a weighted vote for possible activity class centre. A max-margin frame work is applied to learn the feature codebook weight. For activity detection, peaks in the Hough voting space are taken into account and initial event hypothesis is generated using the spatio-temporal information of the participating STIPs. For event recognition a verification Support Vector Machine is used. An extensive evaluation on benchmark large scale video surveillance dataset (VIRAT) and as well on a small scale benchmark dataset (MSR) shows that the proposed method is applicable on a wide range of continuous visual event recognition applications having extremely challenging conditions. | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1077-3142 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ CGR2013 | Serial | 2413 | ||
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| Author | Antoni Gurgui; Debora Gil; Enric Marti | ||||
| Title |
Laplacian Unitary Domain for Texture Morphing | Type | Conference Article | ||
| Year | 2015 | Publication | Proceedings of the 10th International Conference on Computer Vision Theory and Applications VISIGRAPP2015 | Abbreviated Journal | |
| Volume | 1 | Issue | Pages | 693-699 | |
| Keywords | Facial; metamorphosis;LaplacianMorphing | ||||
| Abstract | Deformation of expressive textures is the gateway to realistic computer synthesis of expressions. By their good mathematical properties and flexible formulation on irregular meshes, most texture mappings rely on solutions to the Laplacian in the cartesian space. In the context of facial expression morphing, this approximation can be seen from the opposite point of view by neglecting the metric. In this paper, we use the properties of the Laplacian in manifolds to present a novel approach to warping expressive facial images in order to generate a morphing between them. | ||||
| Address | Munich; Germany; February 2015 | ||||
| Corporate Author | Thesis | ||||
| Publisher | SciTePress | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-989-758-089-5 | Medium | ||
| Area | Expedition | Conference | VISAPP | ||
| Notes | IAM; 600.075 | Approved | no | ||
| Call Number | Admin @ si @ GGM2015 | Serial | 2614 | ||
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| Author | Naveen Onkarappa; Angel Sappa | ||||
| Title |
Laplacian Derivative based Regularization for Optical Flow Estimation in Driving Scenario | Type | Conference Article | ||
| Year | 2013 | Publication | 15th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | |
| Volume | 8048 | Issue | Pages | 483-490 | |
| Keywords | Optical flow; regularization; Driver Assistance Systems; Performance Evaluation | ||||
| Abstract | Existing state of the art optical flow approaches, which are evaluated on standard datasets such as Middlebury, not necessarily have a similar performance when evaluated on driving scenarios. This drop on performance is due to several challenges arising on real scenarios during driving. Towards this direction, in this paper, we propose a modification to the regularization term in a variational optical flow formulation, that notably improves the results, specially in driving scenarios. The proposed modification consists on using the Laplacian derivatives of flow components in the regularization term instead of gradients of flow components. We show the improvements in results on a standard real image sequences dataset (KITTI). | ||||
| Address | York; UK; August 2013 | ||||
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| 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 | 978-3-642-40245-6 | Medium | |
| Area | Expedition | Conference | CAIP | ||
| Notes | ADAS; 600.055; 601.215 | Approved | no | ||
| Call Number | Admin @ si @ OnS2013b | Serial | 2244 | ||
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| Author | David Lloret; C. Mariño; Joan Serrat; Antonio Lopez; Juan J. Villanueva | ||||
| Title |
Landmark-based registration of full SLO video sequences. | Type | Miscellaneous | ||
| Year | 2001 | Publication | Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis,1:189–194. | Abbreviated Journal | |
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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ LMS2001 | Serial | 116 | ||
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| Author | Arturo Fuentes; F. Javier Sanchez; Thomas Voncina; Jorge Bernal | ||||
| Title |
LAMV: Learning to Predict Where Spectators Look in Live Music Performances | Type | Conference Article | ||
| Year | 2021 | Publication | 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications | Abbreviated Journal | |
| Volume | 5 | Issue | Pages | 500-507 | |
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| Abstract | The advent of artificial intelligence has supposed an evolution on how different daily work tasks are performed. The analysis of cultural content has seen a huge boost by the development of computer-assisted methods that allows easy and transparent data access. In our case, we deal with the automation of the production of live shows, like music concerts, aiming to develop a system that can indicate the producer which camera to show based on what each of them is showing. In this context, we consider that is essential to understand where spectators look and what they are interested in so the computational method can learn from this information. The work that we present here shows the results of a first preliminary study in which we compare areas of interest defined by human beings and those indicated by an automatic system. Our system is based on the extraction of motion textures from dynamic Spatio-Temporal Volumes (STV) and then analyzing the patterns by means of texture analysis techniques. We validate our approach over several video sequences that have been labeled by 16 different experts. Our method is able to match those relevant areas identified by the experts, achieving recall scores higher than 80% when a distance of 80 pixels between method and ground truth is considered. Current performance shows promise when detecting abnormal peaks and movement trends. | ||||
| Address | Virtual; February 2021 | ||||
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| Area | Expedition | Conference | VISIGRAPP | ||
| Notes | MV; ISE; 600.119; | Approved | no | ||
| Call Number | Admin @ si @ FSV2021 | Serial | 3570 | ||
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| Author | Naila Murray; Eduard Vazquez | ||||
| Title |
Lacuna Restoration: How to choose a neutral colour? | Type | Conference Article | ||
| Year | 2010 | Publication | Proceedings of The CREATE 2010 Conference | Abbreviated Journal | |
| Volume | Issue | Pages | 248–252 | ||
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| Abstract | Painting restoration which involves filling in material loss (called lacuna) is a complex process. Several standard techniques exist to tackle lacuna restoration,
and this article focuses on those techniques that employ a “neutral” colour to mask the defect. Restoration experts often disagree on the choice of such a colour and in fact, the concept of a neutral colour is controversial. We posit that a neutral colour is one that attracts relatively little visual attention for a specific lacuna. We conducted an eye tracking experiment to compare two common neutral colour selection methods, specifically the most common local colour and the mean local colour. Results obtained demonstrate that the most common local colour triggers less visual attention in general. Notwithstanding, we have observed instances in which the most common colour triggers a significant amount of attention when subjects spent time resolving their confusion about whether or not a lacuna was part of the painting. |
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| Address | Gjovik, Norway | ||||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | CREATE | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ MuV2010 | Serial | 1297 | ||
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| Author | Oualid M. Benkarim; Petia Radeva; Laura Igual | ||||
| Title |
Label Consistent Multiclass Discriminative Dictionary Learning for MRI Segmentation | Type | Conference Article | ||
| Year | 2014 | Publication | 8th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
| Volume | 8563 | Issue | Pages | 138-147 | |
| Keywords | MRI segmentation; sparse representation; discriminative dic- tionary learning; multiclass classi cation | ||||
| Abstract | The automatic segmentation of multiple subcortical structures in brain Magnetic Resonance Images (MRI) still remains a challenging task. In this paper, we address this problem using sparse representation and discriminative dictionary learning, which have shown promising results in compression, image denoising and recently in MRI segmentation. Particularly, we use multiclass dictionaries learned from a set of brain atlases to simultaneously segment multiple subcortical structures.
We also impose dictionary atoms to be specialized in one given class using label consistent K-SVD, which can alleviate the bias produced by unbalanced libraries, present when dealing with small structures. The proposed method is compared with other state of the art approaches for the segmentation of the Basal Ganglia of 35 subjects of a public dataset. The promising results of the segmentation method show the eciency of the multiclass discriminative dictionary learning algorithms in MRI segmentation problems. |
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| Address | Palma de Mallorca; July 2014 | ||||
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| Publisher | Springer International Publishing | 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 | 978-3-319-08848-8 | Medium | |
| Area | Expedition | Conference | AMDO | ||
| Notes | MILAB; OR | Approved | no | ||
| Call Number | Admin @ si @ BRI2014 | Serial | 2494 | ||
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| Author | Oriol Vicente; Alicia Fornes; Ramon Valdes | ||||
| Title |
La Xarxa d Humanitats Digitals de la UABCie: una estructura inteligente para la investigación y la transferencia en Humanidades | Type | Conference Article | ||
| Year | 2017 | Publication | 3rd Congreso Internacional de Humanidades Digitales Hispánicas. Sociedad Internacional | Abbreviated Journal | |
| Volume | Issue | Pages | 281-383 | ||
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| ISSN | ISBN | 978-84-697-5692-8 | Medium | ||
| Area | Expedition | Conference | HDH | ||
| Notes | DAG; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ VFV2017 | Serial | 3060 | ||
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| Author | Alicia Fornes; Josep Llados; Oriol Ramos Terrades; Marçal Rusiñol | ||||
| Title |
La Visió per Computador com a Eina per a la Interpretació Automàtica de Fonts Documentals | Type | Journal | ||
| Year | 2016 | Publication | Lligall, Revista Catalana d'Arxivística | Abbreviated Journal | |
| Volume | 39 | Issue | Pages | 20-46 | |
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| Notes | DAG; 600.097 | Approved | no | ||
| Call Number | Admin @ si @ FLR2016 | Serial | 2897 | ||
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| Author | Robert Benavente; C. Alejandro Parraga; Maria Vanrell | ||||
| Title |
La influencia del contexto en la definicion de las fronteras entre las categorias cromaticas | Type | Conference Article | ||
| Year | 2010 | Publication | 9th Congreso Nacional del Color | Abbreviated Journal | |
| Volume | Issue | Pages | 92–95 | ||
| Keywords | Categorización del color; Apariencia del color; Influencia del contexto; Patrones de Mondrian; Modelos paramétricos | ||||
| Abstract | En este artículo presentamos los resultados de un experimento de categorización de color en el que las muestras se presentaron sobre un fondo multicolor (Mondrian) para simular los efectos del contexto. Los resultados se comparan con los de un experimento previo que, utilizando un paradigma diferente, determinó las fronteras sin tener en cuenta el contexto. El análisis de los resultados muestra que las fronteras obtenidas con el experimento en contexto presentan menos confusión que las obtenidas en el experimento sin contexto. | ||||
| Address | Alicante (Spain) | ||||
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| ISSN | ISBN | 978-84-9717-144-1 | Medium | ||
| Area | Expedition | Conference | CNC | ||
| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ BPV2010 | Serial | 1327 | ||
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| Author | Jian Yang; Alejandro F. Frangi; Jing-Yu Yang; David Zhang; Zhong Jin | ||||
| Title |
KPCA Plus LDA: A Complete Kernel Fisher Discriminant Framework for Feature Extraction and Recognition | Type | Journal | ||
| Year | 2005 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(2):230–244 (IF: 3.810) | Abbreviated Journal | |
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| Notes | Approved | no | |||
| Call Number | Admin @ si @ YFY2005a | Serial | 516 | ||
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| Author | Edgar Riba; D. Mishkin; Daniel Ponsa; E. Rublee; G. Bradski | ||||
| Title |
Kornia: an Open Source Differentiable Computer Vision Library for PyTorch | Type | Conference Article | ||
| Year | 2020 | Publication | IEEE Winter Conference on Applications of Computer Vision | Abbreviated Journal | |
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| Address | Aspen; Colorado; USA; March 2020 | ||||
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| Area | Expedition | Conference | WACV | ||
| Notes | MSIAU; 600.122; 600.130 | Approved | no | ||
| Call Number | Admin @ si @ RMP2020 | Serial | 3291 | ||
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| Author | Christophe Rigaud; Clement Guerin; Dimosthenis Karatzas; Jean-Christophe Burie; Jean-Marc Ogier | ||||
| Title |
Knowledge-driven understanding of images in comic books | Type | Journal Article | ||
| Year | 2015 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
| Volume | 18 | Issue | 3 | Pages | 199-221 |
| Keywords | Document Understanding; comics analysis; expert system | ||||
| Abstract | Document analysis is an active field of research, which can attain a complete understanding of the semantics of a given document. One example of the document understanding process is enabling a computer to identify the key elements of a comic book story and arrange them according to a predefined domain knowledge. In this study, we propose a knowledge-driven system that can interact with bottom-up and top-down information to progressively understand the content of a document. We model the comic book’s and the image processing domains knowledge for information consistency analysis. In addition, different image processing methods are improved or developed to extract panels, balloons, tails, texts, comic characters and their semantic relations in an unsupervised way. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1433-2833 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; 600.056; 600.077 | Approved | no | ||
| Call Number | RGK2015 | Serial | 2595 | ||
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| Author | B. Gautam; Oriol Ramos Terrades; Joana Maria Pujadas-Mora; Miquel Valls-Figols | ||||
| Title |
Knowledge graph based methods for record linkage | Type | Journal Article | ||
| Year | 2020 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 136 | Issue | Pages | 127-133 | |
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| Abstract | Nowadays, it is common in Historical Demography the use of individual-level data as a consequence of a predominant life-course approach for the understanding of the demographic behaviour, family transition, mobility, etc. Advanced record linkage is key since it allows increasing the data complexity and its volume to be analyzed. However, current methods are constrained to link data from the same kind of sources. Knowledge graph are flexible semantic representations, which allow to encode data variability and semantic relations in a structured manner.
In this paper we propose the use of knowledge graph methods to tackle record linkage tasks. The proposed method, named WERL, takes advantage of the main knowledge graph properties and learns embedding vectors to encode census information. These embeddings are properly weighted to maximize the record linkage performance. We have evaluated this method on benchmark data sets and we have compared it to related methods with stimulating and satisfactory results. |
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| Notes | DAG; 600.140; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ GRP2020 | Serial | 3453 | ||
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