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| Author | Josep Llados; Marçal Rusiñol; Alicia Fornes; David Fernandez; Anjan Dutta | ||||
| Title | On the Influence of Word Representations for Handwritten Word Spotting in Historical Documents | Type | Journal Article | ||
| Year | 2012 | Publication | International Journal of Pattern Recognition and Artificial Intelligence | Abbreviated Journal | IJPRAI |
| Volume | 26 | Issue | 5 | Pages | 1263002-126027 |
| Keywords | Handwriting recognition; word spotting; historical documents; feature representation; shape descriptors Read More: http://www.worldscientific.com/doi/abs/10.1142/S0218001412630025 | ||||
| Abstract | 0,624 JCR
Word spotting is the process of retrieving all instances of a queried keyword from a digital library of document images. In this paper we evaluate the performance of different word descriptors to assess the advantages and disadvantages of statistical and structural models in a framework of query-by-example word spotting in historical documents. We compare four word representation models, namely sequence alignment using DTW as a baseline reference, a bag of visual words approach as statistical model, a pseudo-structural model based on a Loci features representation, and a structural approach where words are represented by graphs. The four approaches have been tested with two collections of historical data: the George Washington database and the marriage records from the Barcelona Cathedral. We experimentally demonstrate that statistical representations generally give a better performance, however it cannot be neglected that large descriptors are difficult to be implemented in a retrieval scenario where word spotting requires the indexation of data with million word images. |
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| Call Number | Admin @ si @ LRF2012 | Serial | 2128 | ||
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| Author | Alicia Fornes; Anjan Dutta; Albert Gordo; Josep Llados | ||||
| Title | CVC-MUSCIMA: A Ground-Truth of Handwritten Music Score Images for Writer Identification and Staff Removal | Type | Journal Article | ||
| Year | 2012 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
| Volume | 15 | Issue | 3 | Pages | 243-251 |
| Keywords | Music scores; Handwritten documents; Writer identification; Staff removal; Performance evaluation; Graphics recognition; Ground truths | ||||
| Abstract | 0,405JCR
The analysis of music scores has been an active research field in the last decades. However, there are no publicly available databases of handwritten music scores for the research community. In this paper we present the CVC-MUSCIMA database and ground-truth of handwritten music score images. The dataset consists of 1,000 music sheets written by 50 different musicians. It has been especially designed for writer identification and staff removal tasks. In addition to the description of the dataset, ground-truth, partitioning and evaluation metrics, we also provide some base-line results for easing the comparison between different approaches. |
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| ISSN | 1433-2833 | ISBN | Medium | ||
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| Call Number | Admin @ si @ FDG2012 | Serial | 2129 | ||
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| Author | Susana Alvarez; Maria Vanrell | ||||
| Title | Texton theory revisited: a bag-of-words approach to combine textons | Type | Journal Article | ||
| Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 45 | Issue | 12 | Pages | 4312-4325 |
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| Abstract | The aim of this paper is to revisit an old theory of texture perception and
update its computational implementation by extending it to colour. With this in mind we try to capture the optimality of perceptual systems. This is achieved in the proposed approach by sharing well-known early stages of the visual processes and extracting low-dimensional features that perfectly encode adequate properties for a large variety of textures without needing further learning stages. We propose several descriptors in a bag-of-words framework that are derived from different quantisation models on to the feature spaces. Our perceptual features are directly given by the shape and colour attributes of image blobs, which are the textons. In this way we avoid learning visual words and directly build the vocabularies on these lowdimensionaltexton spaces. Main differences between proposed descriptors rely on how co-occurrence of blob attributes is represented in the vocabularies. Our approach overcomes current state-of-art in colour texture description which is proved in several experiments on large texture datasets. |
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| ISSN | 0031-3203 | ISBN | Medium | ||
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| Notes | CIC | Approved |
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| Call Number | Admin @ si @ AlV2012a | Serial | 2130 | ||
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| Author | Javier Vazquez; Robert Benavente; Maria Vanrell | ||||
| Title | Naming constraints constancy | Type | Conference Article | ||
| Year | 2012 | Publication | 2nd Joint AVA / BMVA Meeting on Biological and Machine Vision | Abbreviated Journal | |
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| Abstract | Different studies have shown that languages from industrialized cultures
share a set of 11 basic colour terms: red, green, blue, yellow, pink, purple, brown, orange, black, white, and grey (Berlin & Kay, 1969, Basic Color Terms, University of California Press)( Kay & Regier, 2003, PNAS, 100, 9085-9089). Some of these studies have also reported the best representatives or focal values of each colour (Boynton and Olson, 1990, Vision Res. 30,1311–1317), (Sturges and Whitfield, 1995, CRA, 20:6, 364–376). Some further studies have provided us with fuzzy datasets for color naming by asking human observers to rate colours in terms of membership values (Benavente -et al-, 2006, CRA. 31:1, 48–56,). Recently, a computational model based on these human ratings has been developed (Benavente -et al-, 2008, JOSA-A, 25:10, 2582-2593). This computational model follows a fuzzy approach to assign a colour name to a particular RGB value. For example, a pixel with a value (255,0,0) will be named 'red' with membership 1, while a cyan pixel with a RGB value of (0, 200, 200) will be considered to be 0.5 green and 0.5 blue. In this work, we show how this colour naming paradigm can be applied to different computer vision tasks. In particular, we report results in colour constancy (Vazquez-Corral -et al-, 2012, IEEE TIP, in press) showing that the classical constraints on either illumination or surface reflectance can be substituted by the statistical properties encoded in the colour names. [Supported by projects TIN2010-21771-C02-1, CSD2007-00018]. |
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| Area | Expedition | Conference | AV A | ||
| Notes | CIC | Approved |
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| Call Number | Admin @ si @ VBV2012 | Serial | 2131 | ||
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| Author | Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco | ||||
| Title | An investigation into plausible neural mechanisms related to the the CIWaM computational model for brightness induction | Type | Conference Article | ||
| Year | 2012 | Publication | 2nd Joint AVA / BMVA Meeting on Biological and Machine Vision | Abbreviated Journal | |
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| Abstract | Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. From a purely computational perspective, we built a low-level computational model (CIWaM) of early sensory processing based on multi-resolution wavelets with the aim of replicating brightness and colour (Otazu et al., 2010, Journal of Vision, 10(12):5) induction effects. Furthermore, we successfully used the CIWaM architecture to define a computational saliency model (Murray et al, 2011, CVPR, 433-440; Vanrell et al, submitted to AVA/BMVA'12). From a biological perspective, neurophysiological evidence suggests that perceived brightness information may be explicitly represented in V1. In this work we investigate possible neural mechanisms that offer a plausible explanation for such effects. To this end, we consider the model by Z.Li (Li, 1999, Network:Comput. Neural Syst., 10, 187-212) which is based on biological data and focuses on the part of V1 responsible for contextual influences, namely, layer 2-3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has proven to account for phenomena such as visual saliency, which share with brightness induction the relevant effect of contextual influences (the ones modelled by CIWaM). In the proposed model, the input to the network is derived from a complete multiscale and multiorientation wavelet decomposition taken from the computational model (CIWaM).
This model successfully accounts for well known pyschophysical effects (among them: the White's and modied White's effects, the Todorovic, Chevreul, achromatic ring patterns, and grating induction effects) for static contexts and also for brigthness induction in dynamic contexts defined by modulating the luminance of surrounding areas. From a methodological point of view, we conclude that the results obtained by the computational model (CIWaM) are compatible with the ones obtained by the neurodynamical model proposed here. |
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| Area | Expedition | Conference | AV A | ||
| Notes | CIC | Approved |
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| Call Number | Admin @ si @ OPD2012a | Serial | 2132 | ||
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| Author | Partha Pratim Roy; Umapada Pal; Josep Llados; Mathieu Nicolas Delalandre | ||||
| Title | Multi-oriented touching text character segmentation in graphical documents using dynamic programming | Type | Journal Article | ||
| Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 45 | Issue | 5 | Pages | 1972-1983 |
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| Abstract | 2,292 JCR
The touching character segmentation problem becomes complex when touching strings are multi-oriented. Moreover in graphical documents sometimes characters in a single-touching string have different orientations. Segmentation of such complex touching is more challenging. In this paper, we present a scheme towards the segmentation of English multi-oriented touching strings into individual characters. When two or more characters touch, they generate a big cavity region in the background portion. Based on the convex hull information, at first, we use this background information to find some initial points for segmentation of a touching string into possible primitives (a primitive consists of a single character or part of a character). Next, the primitives are merged to get optimum segmentation. A dynamic programming algorithm is applied for this purpose using the total likelihood of characters as the objective function. A SVM classifier is used to find the likelihood of a character. To consider multi-oriented touching strings the features used in the SVM are invariant to character orientation. Experiments were performed in different databases of real and synthetic touching characters and the results show that the method is efficient in segmenting touching characters of arbitrary orientations and sizes. |
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| ISSN | 0031-3203 | ISBN | Medium | ||
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| Notes | DAG | Approved |
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| Call Number | Admin @ si @ RPL2012a | Serial | 2133 | ||
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| Author | Partha Pratim Roy; Umapada Pal; Josep Llados | ||||
| Title | Text line extraction in graphical documents using background and foreground | Type | Journal Article | ||
| Year | 2012 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
| Volume | 15 | Issue | 3 | Pages | 227-241 |
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| Abstract | 0,405 JCR
In graphical documents (e.g., maps, engineering drawings), artistic documents etc., the text lines are annotated in multiple orientations or curvilinear way to illustrate different locations or symbols. For the optical character recognition of such documents, individual text lines from the documents need to be extracted. In this paper, we propose a novel method to segment such text lines and the method is based on the foreground and background information of the text components. To effectively utilize the background information, a water reservoir concept is used here. In the proposed scheme, at first, individual components are detected and grouped into character clusters in a hierarchical way using size and positional information. Next, the clusters are extended in two extreme sides to determine potential candidate regions. Finally, with the help of these candidate regions, individual lines are extracted. The experimental results are presented on different datasets of graphical documents, camera-based warped documents, noisy images containing seals, etc. The results demonstrate that our approach is robust and invariant to size and orientation of the text lines present in the document. |
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| ISSN | 1433-2833 | ISBN | Medium | ||
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| Notes | DAG | Approved |
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| Call Number | Admin @ si @ RPL2012b | Serial | 2134 | ||
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| Author | Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades | ||||
| Title | Text/graphic separation using a sparse representation with multi-learned dictionaries | Type | Conference Article | ||
| Year | 2012 | Publication | 21st International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Graphics Recognition; Layout Analysis; Document Understandin | ||||
| Abstract | In this paper, we propose a new approach to extract text regions from graphical documents. In our method, we first empirically construct two sequences of learned dictionaries for the text and graphical parts respectively. Then, we compute the sparse representations of all different sizes and non-overlapped document patches in these learned dictionaries. Based on these representations, each patch can be classified into the text or graphic category by comparing its reconstruction errors. Same-sized patches in one category are then merged together to define the corresponding text or graphic layers which are combined to createfinal text/graphic layer. Finally, in a post-processing step, text regions are further filtered out by using some learned thresholds. | ||||
| Address | Tsukuba | ||||
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| Area | Expedition | Conference | ICPR | ||
| Notes | DAG | Approved |
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| Call Number | Admin @ si @ DTR2012a | Serial | 2135 | ||
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| Author | Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades | ||||
| Title | Noise suppression over bi-level graphical documents using a sparse representation | Type | Conference Article | ||
| Year | 2012 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
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| Address | Bordeaux | ||||
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| Area | Expedition | Conference | CIFED | ||
| Notes | DAG | Approved |
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| Call Number | Admin @ si @ DTR2012b | Serial | 2136 | ||
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| Author | Adriana Romero; Simeon Petkov; Carlo Gatta; M.Sabate; Petia Radeva | ||||
| Title | Efficient automatic segmentation of vessels | Type | Conference Article | ||
| Year | 2012 | Publication | 16th Conference on Medical Image Understanding and Analysis | Abbreviated Journal | |
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| Address | Swansea, United Kingdom | ||||
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| Area | Expedition | Conference | MIUA | ||
| Notes | MILAB | Approved |
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| Call Number | Admin @ si @ | Serial | 2137 | ||
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| Author | David Masip; Alexander Todorov; Jordi Vitria | ||||
| Title | The Role of Facial Regions in Evaluating Social Dime | Type | Conference Article | ||
| Year | 2012 | Publication | 12th European Conference on Computer Vision – Workshops and Demonstrations | Abbreviated Journal | |
| Volume | 7584 | Issue | II | Pages | 210-219 |
| Keywords | Workshops and Demonstrations | ||||
| Abstract | Facial trait judgments are an important information cue for people. Recent works in the Psychology field have stated the basis of face evaluation, defining a set of traits that we evaluate from faces (e.g. dominance, trustworthiness, aggressiveness, attractiveness, threatening or intelligence among others). We rapidly infer information from others faces, usually after a short period of time (< 1000ms) we perceive a certain degree of dominance or trustworthiness of another person from the face. Although these perceptions are not necessarily accurate, they influence many important social outcomes (such as the results of the elections or the court decisions). This topic has also attracted the attention of Computer Vision scientists, and recently a computational model to automatically predict trait evaluations from faces has been proposed. These systems try to mimic the human perception by means of applying machine learning classifiers to a set of labeled data. In this paper we perform an experimental study on the specific facial features that trigger the social inferences. Using previous results from the literature, we propose to use simple similarity maps to evaluate which regions of the face influence the most the trait inferences. The correlation analysis is performed using only appearance, and the results from the experiments suggest that each trait is correlated with specific facial characteristics. | ||||
| Address | Florence, Italy | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Andrea Fusiello, Vittorio Murino, Rita Cucchiara | |
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| ISSN | 0302-9743 | ISBN | 978-3-642-33867-0 | Medium | |
| Area | Expedition | Conference | ECCVW | ||
| Notes | OR;MV | Approved |
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| Call Number | Admin @ si @ MTV2012 | Serial | 2171 | ||
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| Author | Pedro Martins; Carlo Gatta; Paulo Carvalho | ||||
| Title | Feature-driven Maximally Stable Extremal Regions | Type | Conference Article | ||
| Year | 2012 | Publication | 7th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | Issue | Pages | 490-497 | ||
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| Area | Expedition | Conference | VISAPP | ||
| Notes | MILAB | Approved |
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| Call Number | Admin @ si @ MGC2012 | Serial | 2139 | ||
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| Author | Pedro Martins; Paulo Carvalho; Carlo Gatta | ||||
| Title | Context Aware Keypoint Extraction for Robust Image Representation | Type | Conference Article | ||
| Year | 2012 | Publication | 23rd British Machine Vision Conference | Abbreviated Journal | |
| Volume | Issue | Pages | 100.1 - 100.12 | ||
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| Area | Expedition | Conference | BMVC | ||
| Notes | MILAB | Approved |
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| Call Number | Admin @ si @ MCG2012a | Serial | 2140 | ||
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| Author | Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin-Yuste; Manel Sabate; Petia Radeva | ||||
| Title | Accurate coronary centerline extraction, caliber estimation and catheter detection in angiographies | Type | Journal Article | ||
| Year | 2012 | Publication | IEEE Transactions on Information Technology in Biomedicine | Abbreviated Journal | TITB |
| Volume | 16 | Issue | 6 | Pages | 1332-1340 |
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| Abstract | Segmentation of coronary arteries in X-Ray angiography is a fundamental tool to evaluate arterial diseases and choose proper coronary treatment. The accurate segmentation of coronary arteries has become an important topic for the registration of different modalities which allows physicians rapid access to different medical imaging information from Computed Tomography (CT) scans or Magnetic Resonance Imaging (MRI). In this paper, we propose an accurate fully automatic algorithm based on Graph-cuts for vessel centerline extraction, caliber estimation, and catheter detection. Vesselness, geodesic paths, and a new multi-scale edgeness map are combined to customize the Graph-cuts approach to the segmentation of tubular structures, by means of a global optimization of the Graph-cuts energy function. Moreover, a novel supervised learning methodology that integrates local and contextual information is proposed for automatic catheter detection. We evaluate the method performance on three datasets coming from different imaging systems. The method performs as good as the expert observer w.r.t. centerline detection and caliber estimation. Moreover, the method discriminates between arteries and catheter with an accuracy of 96.5%, sensitivity of 72%, and precision of 97.4%. | ||||
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| ISSN | 1089-7771 | ISBN | Medium | ||
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| Notes | MILAB;HuPBA | Approved |
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| Call Number | Admin @ si @ HGE2012 | Serial | 2141 | ||
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| Author | Josep M. Gonfaus; Theo Gevers; Arjan Gijsenij; Xavier Roca; Jordi Gonzalez | ||||
| Title | Edge Classification using Photo-Geo metric features | Type | Conference Article | ||
| Year | 2012 | Publication | 21st International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1497 - 1500 | ||
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| Abstract | Edges are caused by several imaging cues such as shadow, material and illumination transitions. Classification methods have been proposed which are solely based on photometric information, ignoring geometry to classify the physical nature of edges in images. In this paper, the aim is to present a novel strategy to handle both photometric and geometric information for edge classification. Photometric information is obtained through the use of quasi-invariants while geometric information is derived from the orientation and contrast of edges. Different combination frameworks are compared with a new principled approach that captures both information into the same descriptor. From large scale experiments on different datasets, it is shown that, in addition to photometric information, the geometry of edges is an important visual cue to distinguish between different edge types. It is concluded that by combining both cues the performance improves by more than 7% for shadows and highlights. | ||||
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| ISSN | 1051-4651 | ISBN | 978-1-4673-2216-4 | Medium | |
| Area | Expedition | Conference | ICPR | ||
| Notes | ISE | Approved |
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| Call Number | Admin @ si @ GGG2012b | Serial | 2142 | ||
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