| Records |
| Author |
Veronica Romero; Alicia Fornes; Nicolas Serrano; Joan Andreu Sanchez; A.H. Toselli; Volkmar Frinken; E. Vidal; Josep Llados |
| Title |
The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition |
Type |
Journal Article |
| Year |
2013 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
46 |
Issue |
6 |
Pages |
1658-1669 |
| Keywords |
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| Abstract |
Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demography studies and genealogical research. Automatic processing of historical documents, however, has mostly been focused on single works of literature and less on social records, which tend to have a distinct layout, structure, and vocabulary. Such information is usually collected by expert demographers that devote a lot of time to manually transcribe them. This paper presents a new database, compiled from a marriage license books collection, to support research in automatic handwriting recognition for historical documents containing social records. Marriage license books are documents that were used for centuries by ecclesiastical institutions to register marriage licenses. Books from this collection are handwritten and span nearly half a millennium until the beginning of the 20th century. In addition, a study is presented about the capability of state-of-the-art handwritten text recognition systems, when applied to the presented database. Baseline results are reported for reference in future studies. |
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Elsevier Science Inc. New York, NY, USA |
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| ISSN |
0031-3203 |
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Expedition |
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Conference |
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| Notes |
DAG; 600.045; 602.006; 605.203 |
Approved |
no |
| Call Number |
Admin @ si @ RFS2013 |
Serial |
2298 |
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| Author |
Joost Van de Weijer; Fahad Shahbaz Khan; Marc Masana |
| Title |
Interactive Visual and Semantic Image Retrieval |
Type |
Book Chapter |
| Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
Abbreviated Journal |
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| Volume |
48 |
Issue |
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Pages |
31-35 |
| Keywords |
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| Abstract |
One direct consequence of recent advances in digital visual data generation and the direct availability of this information through the World-Wide Web, is a urgent demand for efficient image retrieval systems. The objective of image retrieval is to allow users to efficiently browse through this abundance of images. Due to the non-expert nature of the majority of the internet users, such systems should be user friendly, and therefore avoid complex user interfaces. In this chapter we investigate how high-level information provided by recently developed object recognition techniques can improve interactive image retrieval. Wel apply a bagof- word based image representation method to automatically classify images in a number of categories. These additional labels are then applied to improve the image retrieval system. Next to these high-level semantic labels, we also apply a low-level image description to describe the composition and color scheme of the scene. Both descriptions are incorporated in a user feedback image retrieval setting. The main objective is to show that automatic labeling of images with semantic labels can improve image retrieval results. |
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Springer Berlin Heidelberg |
Place of Publication |
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Editor |
Angel Sappa; Jordi Vitria |
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Original Title |
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Series Title |
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Edition |
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| ISSN |
1868-4394 |
ISBN |
978-3-642-35931-6 |
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Conference |
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| Notes |
CIC; 605.203; 600.048 |
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no |
| Call Number |
Admin @ si @ WKC2013 |
Serial |
2284 |
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| Author |
Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez; Michael Felsberg |
| Title |
Coloring Action Recognition in Still Images |
Type |
Journal Article |
| Year |
2013 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
| Volume |
105 |
Issue |
3 |
Pages |
205-221 |
| Keywords |
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| Abstract |
In this article we investigate the problem of human action recognition in static images. By action recognition we intend a class of problems which includes both action classification and action detection (i.e. simultaneous localization and classification). Bag-of-words image representations yield promising results for action classification, and deformable part models perform very well object detection. The representations for action recognition typically use only shape cues and ignore color information. Inspired by the recent success of color in image classification and object detection, we investigate the potential of color for action classification and detection in static images. We perform a comprehensive evaluation of color descriptors and fusion approaches for action recognition. Experiments were conducted on the three datasets most used for benchmarking action recognition in still images: Willow, PASCAL VOC 2010 and Stanford-40. Our experiments demonstrate that incorporating color information considerably improves recognition performance, and that a descriptor based on color names outperforms pure color descriptors. Our experiments demonstrate that late fusion of color and shape information outperforms other approaches on action recognition. Finally, we show that the different color–shape fusion approaches result in complementary information and combining them yields state-of-the-art performance for action classification. |
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Springer US |
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| ISSN |
0920-5691 |
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| Notes |
CIC; ADAS; 600.057; 600.048 |
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no |
| Call Number |
Admin @ si @ KRW2013 |
Serial |
2285 |
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| Author |
Carles Fernandez; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca |
| Title |
Towards Ontological Cognitive System |
Type |
Book Chapter |
| Year |
2013 |
Publication |
Topics in Medical Image Processing and Computational Vision |
Abbreviated Journal |
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| Volume |
8 |
Issue |
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Pages |
87-99 |
| Keywords |
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| Abstract |
The increasing ubiquitousness of digital information in our daily lives has positioned video as a favored information vehicle, and given rise to an astonishing generation of social media and surveillance footage. This raises a series of technological demands for automatic video understanding and management, which together with the compromising attentional limitations of human operators, have motivated the research community to guide its steps towards a better attainment of such capabilities. As a result, current trends on cognitive vision promise to recognize complex events and self-adapt to different environments, while managing and integrating several types of knowledge. Future directions suggest to reinforce the multi-modal fusion of information sources and the communication with end-users. |
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Springer Netherlands |
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Edition |
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| ISSN |
2212-9391 |
ISBN |
978-94-007-0725-2 |
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Conference |
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| Notes |
ISE; 605.203; 302.018; 600.049 |
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no |
| Call Number |
Admin @ si @ FGT2013 |
Serial |
2287 |
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| Author |
Jordi Roca; C. Alejandro Parraga; Maria Vanrell |
| Title |
Chromatic settings and the structural color constancy index |
Type |
Journal Article |
| Year |
2013 |
Publication |
Journal of Vision |
Abbreviated Journal |
JV |
| Volume |
13 |
Issue |
4-3 |
Pages |
1-26 |
| Keywords |
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| Abstract |
Color constancy is usually measured by achromatic setting, asymmetric matching, or color naming paradigms, whose results are interpreted in terms of indexes and models that arguably do not capture the full complexity of the phenomenon. Here we propose a new paradigm, chromatic setting, which allows a more comprehensive characterization of color constancy through the measurement of multiple points in color space under immersive adaptation. We demonstrated its feasibility by assessing the consistency of subjects' responses over time. The paradigm was applied to two-dimensional (2-D) Mondrian stimuli under three different illuminants, and the results were used to fit a set of linear color constancy models. The use of multiple colors improved the precision of more complex linear models compared to the popular diagonal model computed from gray. Our results show that a diagonal plus translation matrix that models mechanisms other than cone gain might be best suited to explain the phenomenon. Additionally, we calculated a number of color constancy indices for several points in color space, and our results suggest that interrelations among colors are not as uniform as previously believed. To account for this variability, we developed a new structural color constancy index that takes into account the magnitude and orientation of the chromatic shift in addition to the interrelations among colors and memory effects. |
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| Notes |
CIC; 600.052; 600.051; 605.203 |
Approved |
no |
| Call Number |
Admin @ si @ RPV2013 |
Serial |
2288 |
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| Author |
Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga |
| Title |
Low-level SpatioChromatic Grouping for Saliency Estimation |
Type |
Journal Article |
| Year |
2013 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
| Volume |
35 |
Issue |
11 |
Pages |
2810-2816 |
| Keywords |
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| Abstract |
We propose a saliency model termed SIM (saliency by induction mechanisms), which is based on a low-level spatiochromatic model that has successfully predicted chromatic induction phenomena. In so doing, we hypothesize that the low-level visual mechanisms that enhance or suppress image detail are also responsible for making some image regions more salient. Moreover, SIM adds geometrical grouplets to enhance complex low-level features such as corners, and suppress relatively simpler features such as edges. Since our model has been fitted on psychophysical chromatic induction data, it is largely nonparametric. SIM outperforms state-of-the-art methods in predicting eye fixations on two datasets and using two metrics. |
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Edition |
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| ISSN |
0162-8828 |
ISBN |
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Expedition |
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Conference |
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| Notes |
CIC; 600.051; 600.052; 605.203 |
Approved |
no |
| Call Number |
Admin @ si @ MVO2013 |
Serial |
2289 |
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| Author |
Albert Gordo |
| Title |
A Cyclic Page Layout Descriptor for Document Classification & Retrieval |
Type |
Report |
| Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
128 |
Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
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| Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
| Publisher |
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Place of Publication |
Bellaterra, Barcelona |
Editor |
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Summary Language |
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Original Title |
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Edition |
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Expedition |
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Conference |
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| Notes |
CIC;DAG |
Approved |
no |
| Call Number |
Admin @ si @ Gor2009 |
Serial |
2387 |
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| Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
| Title |
Embedding of Graphs with Discrete Attributes Via Label Frequencies |
Type |
Journal Article |
| Year |
2013 |
Publication |
International Journal of Pattern Recognition and Artificial Intelligence |
Abbreviated Journal |
IJPRAI |
| Volume |
27 |
Issue |
3 |
Pages |
1360002-1360029 |
| Keywords |
Discrete attributed graphs; graph embedding; graph classification |
| Abstract |
Graph-based representations of patterns are very flexible and powerful, but they are not easily processed due to the lack of learning algorithms in the domain of graphs. Embedding a graph into a vector space solves this problem since graphs are turned into feature vectors and thus all the statistical learning machinery becomes available for graph input patterns. In this work we present a new way of embedding discrete attributed graphs into vector spaces using node and edge label frequencies. The methodology is experimentally tested on graph classification problems, using patterns of different nature, and it is shown to be competitive to state-of-the-art classification algorithms for graphs, while being computationally much more efficient. |
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Conference |
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| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ GVB2013 |
Serial |
2305 |
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| Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados |
| Title |
Multilevel Analysis of Attributed Graphs for Explicit Graph Embedding in Vector Spaces |
Type |
Book Chapter |
| Year |
2013 |
Publication |
Graph Embedding for Pattern Analysis |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1-26 |
| Keywords |
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| Abstract |
Ability to recognize patterns is among the most crucial capabilities of human beings for their survival, which enables them to employ their sophisticated neural and cognitive systems [1], for processing complex audio, visual, smell, touch, and taste signals. Man is the most complex and the best existing system of pattern recognition. Without any explicit thinking, we continuously compare, classify, and identify huge amount of signal data everyday [2], starting from the time we get up in the morning till the last second we fall asleep. This includes recognizing the face of a friend in a crowd, a spoken word embedded in noise, the proper key to lock the door, smell of coffee, the voice of a favorite singer, the recognition of alphabetic characters, and millions of more tasks that we perform on regular basis. |
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| Publisher |
Springer New York |
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Edition |
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ISBN |
978-1-4614-4456-5 |
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Conference |
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| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ LRL2013b |
Serial |
2271 |
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| Author |
Isabel Guitart; Jordi Conesa; Luis Villarejo; Agata Lapedriza; David Masip; Antoni Perez; Elena Planas |
| Title |
Opinion Mining on Educational Resources at the Open University of Catalonia |
Type |
Conference Article |
| Year |
2013 |
Publication |
3rd International Workshop on Adaptive Learning via Interactive, Collaborative and Emotional approaches. In conjunction with CISIS 2013: The 7th International Conference on Complex, Intelligent, and Software Intensive Systems |
Abbreviated Journal |
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Issue |
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Pages |
385 - 390 |
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| Abstract |
In order to make improvements to teaching, it is vital to know what students think of the way they are taught. With that purpose in mind, exhaustively analyzing the forums associated with the subjects taught at the Universitat Oberta de Cataluya (UOC) would be extremely helpful, as the university's students often post comments on their learning experiences in them. Exploiting the content of such forums is not a simple undertaking. The volume of data involved is very large, and performing the task manually would require a great deal of effort from lecturers. As a first step to solve this problem, we propose a tool to automatically analyze the posts in forums of communities of UOC students and teachers, with a view to systematically mining the opinions they contain. This article defines the architecture of such tool and explains how lexical-semantic and language technology resources can be used to that end. For pilot testing purposes, the tool has been used to identify students' opinions on the UOC's Business Intelligence master's degree course during the last two years. The paper discusses the results of such test. The contribution of this paper is twofold. Firstly, it demonstrates the feasibility of using natural language parsing techniques to help teachers to make decisions. Secondly, it introduces a simple tool that can be refined and adapted to a virtual environment for the purpose in question. |
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Edition |
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ISBN |
978-0-7695-4992-7 |
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Conference |
ALICE |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
GCV2013 |
Serial |
2268 |
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| Author |
Jose Manuel Alvarez; Theo Gevers; Ferran Diego; Antonio Lopez |
| Title |
Road Geometry Classification by Adaptative Shape Models |
Type |
Journal Article |
| Year |
2013 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
Abbreviated Journal |
TITS |
| Volume |
14 |
Issue |
1 |
Pages |
459-468 |
| Keywords |
road detection |
| Abstract |
Vision-based road detection is important for different applications in transportation, such as autonomous driving, vehicle collision warning, and pedestrian crossing detection. Common approaches to road detection are based on low-level road appearance (e.g., color or texture) and neglect of the scene geometry and context. Hence, using only low-level features makes these algorithms highly depend on structured roads, road homogeneity, and lighting conditions. Therefore, the aim of this paper is to classify road geometries for road detection through the analysis of scene composition and temporal coherence. Road geometry classification is proposed by building corresponding models from training images containing prototypical road geometries. We propose adaptive shape models where spatial pyramids are steered by the inherent spatial structure of road images. To reduce the influence of lighting variations, invariant features are used. Large-scale experiments show that the proposed road geometry classifier yields a high recognition rate of 73.57% ± 13.1, clearly outperforming other state-of-the-art methods. Including road shape information improves road detection results over existing appearance-based methods. Finally, it is shown that invariant features and temporal information provide robustness against disturbing imaging conditions. |
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Edition |
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| ISSN |
1524-9050 |
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| Notes |
ADAS;ISE |
Approved |
no |
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Admin @ si @ AGD2013;; ADAS @ adas @ |
Serial |
2269 |
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| Author |
Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner |
| Title |
Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation |
Type |
Conference Article |
| Year |
2011 |
Publication |
In Proceedings of the Sixth International Workshop on Digital Technologies in Cartographic Heritage |
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CartoHerit |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ RRL2011b |
Serial |
1978 |
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| Author |
Jon Almazan; Alicia Fornes; Ernest Valveny |
| Title |
A non-rigid appearance model for shape description and recognition |
Type |
Journal Article |
| Year |
2012 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
45 |
Issue |
9 |
Pages |
3105--3113 |
| Keywords |
Shape recognition; Deformable models; Shape modeling; Hand-drawn recognition |
| Abstract |
In this paper we describe a framework to learn a model of shape variability in a set of patterns. The framework is based on the Active Appearance Model (AAM) and permits to combine shape deformations with appearance variability. We have used two modifications of the Blurred Shape Model (BSM) descriptor as basic shape and appearance features to learn the model. These modifications permit to overcome the rigidity of the original BSM, adapting it to the deformations of the shape to be represented. We have applied this framework to representation and classification of handwritten digits and symbols. We show that results of the proposed methodology outperform the original BSM approach. |
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0031-3203 |
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DAG |
Approved |
no |
| Call Number |
DAG @ dag @ AFV2012 |
Serial |
1982 |
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| Author |
Jon Almazan; David Fernandez; Alicia Fornes; Josep Llados; Ernest Valveny |
| Title |
A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection |
Type |
Conference Article |
| Year |
2012 |
Publication |
13th International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
453-458 |
| Keywords |
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| Abstract |
In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase. |
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Original Title |
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Edition |
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ISBN |
978-1-4673-2262-1 |
Medium |
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Expedition |
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Conference |
ICFHR |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ AFF2012 |
Serial |
1983 |
| Permanent link to this record |
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| Author |
Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny |
| Title |
Efficient Exemplar Word Spotting |
Type |
Conference Article |
| Year |
2012 |
Publication |
23rd British Machine Vision Conference |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
67.1- 67.11 |
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| Abstract |
In this paper we propose an unsupervised segmentation-free method for word spotting in document images.
Documents are represented with a grid of HOG descriptors, and a sliding window approach is used to locate the document regions that are most similar to the query. We use the exemplar SVM framework to produce a better representation of the query in an unsupervised way. Finally, the document descriptors are precomputed and compressed with Product Quantization. This offers two advantages: first, a large number of documents can be kept in RAM memory at the same time. Second, the sliding window becomes significantly faster since distances between quantized HOG descriptors can be precomputed. Our results significantly outperform other segmentation-free methods in the literature, both in accuracy and in speed and memory usage. |
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| Corporate Author |
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Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
1-901725-46-4 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
BMVC |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ AGF2012 |
Serial |
1984 |
| Permanent link to this record |
