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Author | Anjan Dutta | ||||
Title | Inexact Subgraph Matching Applied to Symbol Spotting in Graphical Documents | Type | Book Whole | ||
Year | 2014 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | There is a resurgence in the use of structural approaches in the usual object recognition and retrieval problem. Graph theory, in particular, graph matching plays a relevant role in that. Specifically, the detection of an object (or a part of that) in an image in terms of structural features can be formulated as a subgraph matching. Subgraph matching is a challenging task. Specially due to the presence of outliers most of the graph matching algorithms do not perform well in subgraph matching scenario. Also exact subgraph isomorphism has proven to be an NP-complete problem. So naturally, in graph matching community, there are lot of efforts addressing the problem of subgraph matching within suboptimal bound. Most of them work with approximate algorithms that try to get an inexact solution in estimated way. In addition, usual recognition must cope with distortion. Inexact graph matching consists in finding the best isomorphism under a similarity measure. Theoretically this thesis proposes algorithms for solving subgraph matching in an approximate and inexact way.
We consider the symbol spotting problem on graphical documents or line drawings from application point of view. This is a well known problem in the graphics recognition community. It can be further applied for indexing and classification of documents based on their contents. The structural nature of this kind of documents easily motivates one for giving a graph based representation. So the symbol spotting problem on graphical documents can be considered as a subgraph matching problem. The main challenges in this application domain is the noise and distortions that might come during the usage, digitalization and raster to vector conversion of those documents. Apart from that computer vision nowadays is not any more confined within a limited number of images. So dealing a huge number of images with graph based method is a further challenge. In this thesis, on one hand, we have worked on efficient and robust graph representation to cope with the noise and distortions coming from documents. On the other hand, we have worked on different graph based methods and framework to solve the subgraph matching problem in a better approximated way, which can also deal with considerable number of images. Firstly, we propose a symbol spotting method by hashing serialized subgraphs. Graph serialization allows to create factorized substructures such as graph paths, which can be organized in hash tables depending on the structural similarities of the serialized subgraphs. The involvement of hashing techniques helps to reduce the search space substantially and speeds up the spotting procedure. Secondly, we introduce contextual similarities based on the walk based propagation on tensor product graph. These contextual similarities involve higher order information and more reliable than pairwise similarities. We use these higher order similarities to formulate subgraph matching as a node and edge selection problem in the tensor product graph. Thirdly, we propose near convex grouping to form near convex region adjacency graph which eliminates the limitations of traditional region adjacency graph representation for graphic recognition. Fourthly, we propose a hierarchical graph representation by simplifying/correcting the structural errors to create a hierarchical graph of the base graph. Later these hierarchical graph structures are matched with some graph matching methods. Apart from that, in this thesis we have provided an overall experimental comparison of all the methods and some of the state-of-the-art methods. Furthermore, some dataset models have also been proposed. |
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Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Josep Llados;Umapada Pal | |
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ISSN | ISBN | 978-84-940902-4-0 | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ Dut2014 | Serial | 2465 | ||
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Author | Michal Drozdzal; Jordi Vitria; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva | ||||
Title | Intestinal event segmentation for endoluminal video analysis | Type | Conference Article | ||
Year | 2014 | Publication | 21st IEEE International Conference on Image Processing | Abbreviated Journal | |
Volume | Issue | Pages | 3592 - 3596 | ||
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Address | Paris; Francia; October 2014 | ||||
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Area | Expedition | Conference | ICIP | ||
Notes | MILAB; OR;MV | Approved | no | ||
Call Number | Admin @ si @ DVS2014 | Serial | 2565 | ||
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Author | Sergio Escalera; Xavier Baro; Jordi Gonzalez; Miguel Angel Bautista; Meysam Madadi; Miguel Reyes; Victor Ponce; Hugo Jair Escalante; Jaime Shotton; Isabelle Guyon | ||||
Title | ChaLearn Looking at People Challenge 2014: Dataset and Results | Type | Conference Article | ||
Year | 2014 | Publication | ECCV Workshop on ChaLearn Looking at People | Abbreviated Journal | |
Volume | 8925 | Issue | Pages | 459-473 | |
Keywords | Human Pose Recovery; Behavior Analysis; Action and in- teractions; Multi-modal gestures; recognition | ||||
Abstract | This paper summarizes the ChaLearn Looking at People 2014 challenge data and the results obtained by the participants. The competition was split into three independent tracks: human pose recovery from RGB data, action and interaction recognition from RGB data sequences, and multi-modal gesture recognition from RGB-Depth sequences. For all the tracks, the goal was to perform user-independent recognition in sequences of continuous images using the overlapping Jaccard index as the evaluation measure. In this edition of the ChaLearn challenge, two large novel data sets were made publicly available and the Microsoft Codalab platform were used to manage the competition. Outstanding results were achieved in the three challenge tracks, with accuracy results of 0.20, 0.50, and 0.85 for pose recovery, action/interaction recognition, and multi-modal gesture recognition, respectively. | ||||
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Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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Area | Expedition | Conference | ECCVW | ||
Notes | HuPBA; ISE; 600.063;MV | Approved | no | ||
Call Number | Admin @ si @ EBG2014 | Serial | 2529 | ||
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Author | Noha Elfiky; Theo Gevers; Arjan Gijsenij; Jordi Gonzalez | ||||
Title | Color Constancy using 3D Scene Geometry derived from a Single Image | Type | Journal Article | ||
Year | 2014 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
Volume | 23 | Issue | 9 | Pages | 3855-3868 |
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Abstract | The aim of color constancy is to remove the effect of the color of the light source. As color constancy is inherently an ill-posed problem, most of the existing color constancy algorithms are based on specific imaging assumptions (e.g. grey-world and white patch assumption).
In this paper, 3D geometry models are used to determine which color constancy method to use for the different geometrical regions (depth/layer) found in images. The aim is to classify images into stages (rough 3D geometry models). According to stage models; images are divided into stage regions using hard and soft segmentation. After that, the best color constancy methods is selected for each geometry depth. To this end, we propose a method to combine color constancy algorithms by investigating the relation between depth, local image statistics and color constancy. Image statistics are then exploited per depth to select the proper color constancy method. Our approach opens the possibility to estimate multiple illuminations by distinguishing nearby light source from distant illuminations. Experiments on state-of-the-art data sets show that the proposed algorithm outperforms state-of-the-art single color constancy algorithms with an improvement of almost 50% of median angular error. When using a perfect classifier (i.e, all of the test images are correctly classified into stages); the performance of the proposed method achieves an improvement of 52% of the median angular error compared to the best-performing single color constancy algorithm. |
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Series Volume | Series Issue | Edition | |||
ISSN | 1057-7149 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ISE; 600.078 | Approved | no | ||
Call Number | Admin @ si @ EGG2014 | Serial | 2528 | ||
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Author | Antonio Esteban Lansaque | ||||
Title | 3D reconstruction and recognition using structured ligth | Type | Report | ||
Year | 2014 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 179 | Issue | Pages | ||
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Abstract | This work covers the problem of 3D reconstruction, recognition and 6DOF pose estimation. The goal of this project is to reconstruct a 3D scene and to align an object model of the industrial pieces onto the reconstructed scene. The reconstruction algorithm is based on stereo techniques and the recognition algorithm is based on SHOT descriptors computed on a set of uniform keypoints. Correspondences are used to estimate a first 6DOF transformation that maps the model onto the scene and then ICP algorithm is used to refine the transformation. In order to check the effectiveness of the proposed algorithm, several experiments were performed. These experiments were conducted on a lab environment in order to get results under the same conditions in all of them. Although obtained results are not real time results, the proposed algorithm ends up with high rates of object recognition. | ||||
Address | UAB; September 2014 | ||||
Corporate Author | Thesis | Master's thesis | |||
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Area | Expedition | Conference | |||
Notes | IAM; 600.075 | Approved | no | ||
Call Number | Admin @ si @ Est2014 | Serial | 2578 | ||
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Author | David Fernandez; Jon Almazan; Nuria Cirera; Alicia Fornes; Josep Llados | ||||
Title | BH2M: the Barcelona Historical Handwritten Marriages database | Type | Conference Article | ||
Year | 2014 | Publication | 22nd International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 256 - 261 | ||
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Abstract | This paper presents an image database of historical handwritten marriages records stored in the archives of Barcelona cathedral, and the corresponding meta-data addressed to evaluate the performance of document analysis algorithms. The contribution of this paper is twofold. First, it presents a complete ground truth which covers the whole pipeline of handwriting
recognition research, from layout analysis to recognition and understanding. Second, it is the first dataset in the emerging area of genealogical document analysis, where documents are manuscripts pseudo-structured with specific lexicons and the interest is beyond pure transcriptions but context dependent. |
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Address | Creete Island; Grecia; September 2014 | ||||
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Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 1051-4651 | ISBN | Medium | ||
Area | Expedition | Conference | ICPR | ||
Notes | DAG; 600.056; 600.061; 602.006; 600.077 | Approved | no | ||
Call Number | Admin @ si @ FAC2014 | Serial | 2461 | ||
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Author | David Fernandez | ||||
Title | Contextual Word Spotting in Historical Handwritten Documents | Type | Book Whole | ||
Year | 2014 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | There are countless collections of historical documents in archives and libraries that contain plenty of valuable information for historians and researchers. The extraction of this information has become a central task among the Document Analysis researches and practitioners.
There is an increasing interest to digital preserve and provide access to these kind of documents. But only the digitalization is not enough for the researchers. The extraction and/or indexation of information of this documents has had an increased interest among researchers. In many cases, and in particular in historical manuscripts, the full transcription of these documents is extremely dicult due the inherent deciencies: poor physical preservation, dierent writing styles, obsolete languages, etc. Word spotting has become a popular an ecient alternative to full transcription. It inherently involves a high level of degradation in the images. The search of words is holistically formulated as a visual search of a given query shape in a larger image, instead of recognising the input text and searching the query word with an ascii string comparison. But the performance of classical word spotting approaches depend on the degradation level of the images being unacceptable in many cases . In this thesis we have proposed a novel paradigm called contextual word spotting method that uses the contextual/semantic information to achieve acceptable results whereas classical word spotting does not reach. The contextual word spotting framework proposed in this thesis is a segmentation-based word spotting approach, so an ecient word segmentation is needed. Historical handwritten documents present some common diculties that can increase the diculties the extraction of the words. We have proposed a line segmentation approach that formulates the problem as nding the central part path in the area between two consecutive lines. This is solved as a graph traversal problem. A path nding algorithm is used to nd the optimal path in a graph, previously computed, between the text lines. Once the text lines are extracted, words are localized inside the text lines using a word segmentation technique from the state of the art. Classical word spotting approaches can be improved using the contextual information of the documents. We have introduced a new framework, oriented to handwritten documents that present a highly structure, to extract information making use of context. The framework is an ecient tool for semi-automatic transcription that uses the contextual information to achieve better results than classical word spotting approaches. The contextual information is automatically discovered by recognizing repetitive structures and categorizing all the words according to semantic classes. The most frequent words in each semantic cluster are extracted and the same text is used to transcribe all them. The experimental results achieved in this thesis outperform classical word spotting approaches demonstrating the suitability of the proposed ensemble architecture for spotting words in historical handwritten documents using contextual information. |
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Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Josep Llados;Alicia Fornes | |
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-84-940902-7-1 | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ Fer2014 | Serial | 2573 | ||
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Author | Volkmar Frinken; Andreas Fischer; Markus Baumgartner; Horst Bunke | ||||
Title | Keyword spotting for self-training of BLSTM NN based handwriting recognition systems | Type | Journal Article | ||
Year | 2014 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 47 | Issue | 3 | Pages | 1073-1082 |
Keywords | Document retrieval; Keyword spotting; Handwriting recognition; Neural networks; Semi-supervised learning | ||||
Abstract | The automatic transcription of unconstrained continuous handwritten text requires well trained recognition systems. The semi-supervised paradigm introduces the concept of not only using labeled data but also unlabeled data in the learning process. Unlabeled data can be gathered at little or not cost. Hence it has the potential to reduce the need for labeling training data, a tedious and costly process. Given a weak initial recognizer trained on labeled data, self-training can be used to recognize unlabeled data and add words that were recognized with high confidence to the training set for re-training. This process is not trivial and requires great care as far as selecting the elements that are to be added to the training set is concerned. In this paper, we propose to use a bidirectional long short-term memory neural network handwritten recognition system for keyword spotting in order to select new elements. A set of experiments shows the high potential of self-training for bootstrapping handwriting recognition systems, both for modern and historical handwritings, and demonstrate the benefits of using keyword spotting over previously published self-training schemes. | ||||
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Area | Expedition | Conference | |||
Notes | DAG; 600.077; 602.101 | Approved | no | ||
Call Number | Admin @ si @ FFB2014 | Serial | 2297 | ||
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Author | Alicia Fornes; V.C.Kieu; M. Visani; N.Journet; Anjan Dutta | ||||
Title | The ICDAR/GREC 2013 Music Scores Competition: Staff Removal | Type | Book Chapter | ||
Year | 2014 | Publication | Graphics Recognition. Current Trends and Challenges | Abbreviated Journal | |
Volume | 8746 | Issue | Pages | 207-220 | |
Keywords | Competition; Graphics recognition; Music scores; Writer identification; Staff removal | ||||
Abstract | The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated in both staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario concerning old and degraded music scores. For this purpose, we have generated a new set of semi-synthetic images using two degradation models that we previously introduced: local noise and 3D distortions. In this extended paper we provide an extended description of the dataset, degradation models, evaluation metrics, the participant’s methods and the obtained results that could not be presented at ICDAR and GREC proceedings due to page limitations. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | B.Lamiroy; J.-M. Ogier | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-662-44853-3 | Medium | |
Area | Expedition | Conference | |||
Notes | DAG; 600.077; 600.061 | Approved | no | ||
Call Number | Admin @ si @ FKV2014 | Serial | 2581 | ||
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Author | David Fernandez; Josep Llados; Alicia Fornes | ||||
Title | A graph-based approach for segmenting touching lines in historical handwritten documents | Type | Journal Article | ||
Year | 2014 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
Volume | 17 | Issue | 3 | Pages | 293-312 |
Keywords | Text line segmentation; Handwritten documents; Document image processing; Historical document analysis | ||||
Abstract | Text line segmentation in handwritten documents is an important task in the recognition of historical documents. Handwritten document images contain text lines with multiple orientations, touching and overlapping characters between consecutive text lines and different document structures, making line segmentation a difficult task. In this paper, we present a new approach for handwritten text line segmentation solving the problems of touching components, curvilinear text lines and horizontally overlapping components. The proposed algorithm formulates line segmentation as finding the central path in the area between two consecutive lines. This is solved as a graph traversal problem. A graph is constructed using the skeleton of the image. Then, a path-finding algorithm is used to find the optimum path between text lines. The proposed algorithm has been evaluated on a comprehensive dataset consisting of five databases: ICDAR2009, ICDAR2013, UMD, the George Washington and the Barcelona Marriages Database. The proposed method outperforms the state-of-the-art considering the different types and difficulties of the benchmarking data. | ||||
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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; 600.061; 602.006; 600.077 | Approved | no | ||
Call Number | Admin @ si @ FLF2014 | Serial | 2459 | ||
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Author | Alicia Fornes; Josep Llados; Joan Mas; Joana Maria Pujadas-Mora; Anna Cabre | ||||
Title | A Bimodal Crowdsourcing Platform for Demographic Historical Manuscripts | Type | Conference Article | ||
Year | 2014 | Publication | Digital Access to Textual Cultural Heritage Conference | Abbreviated Journal | |
Volume | Issue | Pages | 103-108 | ||
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Abstract | In this paper we present a crowdsourcing web-based application for extracting information from demographic handwritten document images. The proposed application integrates two points of view: the semantic information for demographic research, and the ground-truthing for document analysis research. Concretely, the application has the contents view, where the information is recorded into forms, and the labeling view, with the word labels for evaluating document analysis techniques. The crowdsourcing architecture allows to accelerate the information extraction (many users can work simultaneously), validate the information, and easily provide feedback to the users. We finally show how the proposed application can be extended to other kind of demographic historical manuscripts. | ||||
Address | Madrid; May 2014 | ||||
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ISSN | ISBN | 978-1-4503-2588-2 | Medium | ||
Area | Expedition | Conference | DATeCH | ||
Notes | DAG; 600.061; 602.006; 600.077 | Approved | no | ||
Call Number | Admin @ si @ FLM2014 | Serial | 2516 | ||
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Author | David Fernandez; R.Manmatha; Josep Llados; Alicia Fornes | ||||
Title | Sequential Word Spotting in Historical Handwritten Documents | Type | Conference Article | ||
Year | 2014 | Publication | 11th IAPR International Workshop on Document Analysis and Systems | Abbreviated Journal | |
Volume | Issue | Pages | 101 - 105 | ||
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Abstract | In this work we present a handwritten word spotting approach that takes advantage of the a priori known order of appearance of the query words. Given an ordered sequence of query word instances, the proposed approach performs a
sequence alignment with the words in the target collection. Although the alignment is quite sparse, i.e. the number of words in the database is higher than the query set, the improvement in the overall performance is sensitively higher than isolated word spotting. As application dataset, we use a collection of handwritten marriage licenses taking advantage of the ordered index pages of family names. |
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Address | Tours; Francia; April 2014 | ||||
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Publisher | Place of Publication | Editor | |||
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ISSN | ISBN | 978-1-4799-3243-6 | Medium | ||
Area | Expedition | Conference | DAS | ||
Notes | DAG; 600.061; 600.056; 602.006; 600.077 | Approved | no | ||
Call Number | Admin @ si @ FML2014 | Serial | 2462 | ||
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Author | Alicia Fornes; Gemma Sanchez | ||||
Title | Analysis and Recognition of Music Scores | Type | Book Chapter | ||
Year | 2014 | Publication | Handbook of Document Image Processing and Recognition | Abbreviated Journal | |
Volume | E | Issue | Pages | 749-774 | |
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Abstract | The analysis and recognition of music scores has attracted the interest of researchers for decades. Optical Music Recognition (OMR) is a classical research field of Document Image Analysis and Recognition (DIAR), whose aim is to extract information from music scores. Music scores contain both graphical and textual information, and for this reason, techniques are closely related to graphics recognition and text recognition. Since music scores use a particular diagrammatic notation that follow the rules of music theory, many approaches make use of context information to guide the recognition and solve ambiguities. This chapter overviews the main Optical Music Recognition (OMR) approaches. Firstly, the different methods are grouped according to the OMR stages, namely, staff removal, music symbol recognition, and syntactical analysis. Secondly, specific approaches for old and handwritten music scores are reviewed. Finally, online approaches and commercial systems are also commented. | ||||
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Publisher | Springer London | Place of Publication | Editor | D. Doermann; K. Tombre | |
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ISSN | ISBN | 978-0-85729-860-7 | Medium | ||
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Notes | DAG; ADAS; 600.076; 600.077 | Approved | no | ||
Call Number | Admin @ si @ FoS2014 | Serial | 2484 | ||
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Author | David Fernandez; Pau Riba; Alicia Fornes; Josep Llados | ||||
Title | On the Influence of Key Point Encoding for Handwritten Word Spotting | Type | Conference Article | ||
Year | 2014 | Publication | 14th International Conference on Frontiers in Handwriting Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 476 - 481 | ||
Keywords | Local descriptors; Interest points; Handwritten documents; Word spotting; Historical document analysis | ||||
Abstract | In this paper we evaluate the influence of the selection of key points and the associated features in the performance of word spotting processes. In general, features can be extracted from a number of characteristic points like corners, contours, skeletons, maxima, minima, crossings, etc. A number of descriptors exist in the literature using different interest point detectors. But the intrinsic variability of handwriting vary strongly on the performance if the interest points are not stable enough. In this paper, we analyze the performance of different descriptors for local interest points. As benchmarking dataset we have used the Barcelona Marriage Database that contains handwritten records of marriages over five centuries. | ||||
Address | Creete Island; Grecia; September 2014 | ||||
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ISSN | 2167-6445 | ISBN | 978-1-4799-4335-7 | Medium | |
Area | Expedition | Conference | ICFHR | ||
Notes | DAG; 600.056; 600.061; 602.006; 600.077 | Approved | no | ||
Call Number | Admin @ si @ FRF2014 | Serial | 2460 | ||
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Author | Onur Ferhat; Fernando Vilariño; F. Javier Sanchez | ||||
Title | A cheap portable eye-tracker solution for common setups. | Type | Journal Article | ||
Year | 2014 | Publication | Journal of Eye Movement Research | Abbreviated Journal | JEMR |
Volume | 7 | Issue | 3 | Pages | 1-10 |
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Abstract | We analyze the feasibility of a cheap eye-tracker where the hardware consists of a single webcam and a Raspberry Pi device. Our aim is to discover the limits of such a system and to see whether it provides an acceptable performance. We base our work on the open source Opengazer (Zielinski, 2013) and we propose several improvements to create a robust, real-time system which can work on a computer with 30Hz sampling rate. After assessing the accuracy of our eye-tracker in elaborated experiments involving 12 subjects under 4 different system setups, we install it on a Raspberry Pi to create a portable stand-alone eye-tracker which achieves 1.42° horizontal accuracy with 3Hz refresh rate for a building cost of 70 Euros. | ||||
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Notes | ;SIAI | Approved | no | ||
Call Number | Admin @ si @ FVS2014 | Serial | 2435 | ||
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