Records |
Author |
Ivet Rafegas |
Title |
Exploring Low-Level Vision Models. Case Study: Saliency Prediction |
Type |
Report |
Year |
2013 |
Publication |
CVC Technical Report |
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175 |
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Admin @ si @ Raf2013 |
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2409 |
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Author |
Francesco Brughi |
Title |
Artistic Heritage Motive Retrieval: an Explorative Study |
Type |
Report |
Year |
2013 |
Publication |
CVC Technical Report |
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176 |
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IAM |
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Admin @ si @ Bru2013 |
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2410 |
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Author |
Joan Mas; Gemma Sanchez; Josep Llados |
Title |
SSP: Sketching slide Presentations, a Syntactic Approach |
Type |
Book Chapter |
Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
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6020 |
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118-129 |
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The design of a slide presentation is a creative process. In this process first, humans visualize in their minds what they want to explain. Then, they have to be able to represent this knowledge in an understandable way. There exists a lot of commercial software that allows to create our own slide presentations but the creativity of the user is rather limited. In this article we present an application that allows the user to create and visualize a slide presentation from a sketch. A slide may be seen as a graphical document or a diagram where its elements are placed in a particular spatial arrangement. To describe and recognize slides a syntactic approach is proposed. This approach is based on an Adjacency Grammar and a parsing methodology to cope with this kind of grammars. The experimental evaluation shows the performance of our methodology from a qualitative and a quantitative point of view. Six different slides containing different number of symbols, from 4 to 7, have been given to the users and they have drawn them without restrictions in the order of the elements. The quantitative results give an idea on how suitable is our methodology to describe and recognize the different elements in a slide. |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-13727-3 |
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GREC |
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DAG |
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MSL2010 |
Serial |
2405 |
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Author |
Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman |
Title |
A Performance Characterization Algorithm for Symbol Localization |
Type |
Book Chapter |
Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
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6020 |
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260–271 |
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In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols). |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-13727-3 |
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GREC |
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DAG |
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no |
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Admin @ si @ DRV2010 |
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2406 |
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Author |
Marçal Rusiñol; K. Bertet; Jean-Marc Ogier; Josep Llados |
Title |
Symbol Recognition Using a Concept Lattice of Graphical Patterns |
Type |
Book Chapter |
Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
Abbreviated Journal |
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Volume |
6020 |
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Pages |
187-198 |
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Abstract |
In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-13727-3 |
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DAG |
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no |
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Admin @ si @ RBO2010 |
Serial |
2407 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
Title |
Touching Text Character Localization in Graphical Documents using SIFT |
Type |
Book Chapter |
Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
Abbreviated Journal |
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Volume |
6020 |
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Pages |
199-211 |
Keywords |
Support Vector Machine; Text Component; Graphical Line; Document Image; Scale Invariant Feature Transform |
Abstract |
Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult.
Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-13727-3 |
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DAG |
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no |
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Admin @ si @ RPL2010c |
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2408 |
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Author |
German Ros |
Title |
Visual SLAM for Driverless Cars: An Initial Survey |
Type |
Report |
Year |
2012 |
Publication |
CVC Technical Report |
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Volume |
170 |
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ADAS |
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no |
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Admin @ si @ Ros2012c |
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2414 |
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Author |
Xu Hu |
Title |
Real-Time Part Based Models for Object Detection |
Type |
Report |
Year |
2012 |
Publication |
CVC Technical Report |
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Volume |
171 |
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ADAS;ISE |
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no |
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Admin @ si @ Hu2012 |
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2415 |
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Author |
Nuria Cirera |
Title |
Recognition of Handwritten Historical Documents |
Type |
Report |
Year |
2012 |
Publication |
CVC Technical Report |
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174 |
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no |
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Admin @ si @ Cir2012 |
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2416 |
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Author |
Adria Ruiz; Joost Van de Weijer; Xavier Binefa |
Title |
Regularized Multi-Concept MIL for weakly-supervised facial behavior categorization |
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Conference Article |
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2014 |
Publication |
25th British Machine Vision Conference |
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We address the problem of estimating high-level semantic labels for videos of recorded people by means of analysing their facial expressions. This problem, to which we refer as facial behavior categorization, is a weakly-supervised learning problem where we do not have access to frame-by-frame facial gesture annotations but only weak-labels at the video level are available. Therefore, the goal is to learn a set of discriminative expressions and how they determine the video weak-labels. Facial behavior categorization can be posed as a Multi-Instance-Learning (MIL) problem and we propose a novel MIL method called Regularized Multi-Concept MIL to solve it. In contrast to previous approaches applied in facial behavior analysis, RMC-MIL follows a Multi-Concept assumption which allows different facial expressions (concepts) to contribute differently to the video-label. Moreover, to handle with the high-dimensional nature of facial-descriptors, RMC-MIL uses a discriminative approach to model the concepts and structured sparsity regularization to discard non-informative features. RMC-MIL is posed as a convex-constrained optimization problem where all the parameters are jointly learned using the Projected-Quasi-Newton method. In our experiments, we use two public data-sets to show the advantages of the Regularized Multi-Concept approach and its improvement compared to existing MIL methods. RMC-MIL outperforms state-of-the-art results in the UNBC data-set for pain detection. |
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Nottingham; UK; September 2014 |
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BMVC |
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LAMP; CIC; 600.074; 600.079 |
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no |
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Admin @ si @ RWB2014 |
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2508 |
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Author |
Ferran Poveda |
Title |
Computer Graphics and Vision Techniques for the Study of the Muscular Fiber Architecture of the Myocardium |
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Book Whole |
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2013 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Ph.D. thesis |
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Debora Gil;Enric Marti |
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IAM |
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no |
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Admin @ si @ Pov2013 |
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2417 |
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Author |
Miquel Ferrer; I. Bardaji; Ernest Valveny; Dimosthenis Karatzas; Horst Bunke |
Title |
Median Graph Computation by Means of Graph Embedding into Vector Spaces |
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Book Chapter |
Year |
2013 |
Publication |
Graph Embedding for Pattern Analysis |
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45-72 |
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In pattern recognition [8, 14], a key issue to be addressed when designing a system is how to represent input patterns. Feature vectors is a common option. That is, a set of numerical features describing relevant properties of the pattern are computed and arranged in a vector form. The main advantages of this kind of representation are computational simplicity and a well sound mathematical foundation. Thus, a large number of operations are available to work with vectors and a large repository of algorithms for pattern analysis and classification exist. However, the simple structure of feature vectors might not be the best option for complex patterns where nonnumerical features or relations between different parts of the pattern become relevant. |
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Springer New York |
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Yun Fu; Yungian Ma |
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978-1-4614-4456-5 |
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DAG |
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no |
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Admin @ si @ FBV2013 |
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2421 |
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Author |
Mirko Arnold; Anarta Ghosh; Gerard Lacey; Stephen Patchett; Hugh Mulcahy |
Title |
Indistinct frame detection in colonoscopy videos |
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Conference Article |
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2009 |
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Machine Vision and Image Processing Conference |
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47-52 |
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800 |
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MV |
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no |
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fernando @ fernando @ |
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2424 |
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Author |
A.Kesidis; Dimosthenis Karatzas |
Title |
Logo and Trademark Recognition |
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Book Chapter |
Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
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D |
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591-646 |
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Logo recognition; Logo removal; Logo spotting; Trademark registration; Trademark retrieval systems |
Abstract |
The importance of logos and trademarks in nowadays society is indisputable, variably seen under a positive light as a valuable service for consumers or a negative one as a catalyst of ever-increasing consumerism. This chapter discusses the technical approaches for enabling machines to work with logos, looking into the latest methodologies for logo detection, localization, representation, recognition, retrieval, and spotting in a variety of media. This analysis is presented in the context of three different applications covering the complete depth and breadth of state of the art techniques. These are trademark retrieval systems, logo recognition in document images, and logo detection and removal in images and videos. This chapter, due to the very nature of logos and trademarks, brings together various facets of document image analysis spanning graphical and textual content, while it links document image analysis to other computer vision domains, especially when it comes to the analysis of real-scene videos and images. |
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Springer London |
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D. Doermann; K. Tombre |
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978-0-85729-858-4 |
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DAG; 600.077 |
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no |
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Admin @ si @ KeK2014 |
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2425 |
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Author |
Mirko Arnold; Stephan Ameling; Anarta Ghosh; Gerard Lacey |
Title |
Quality Improvement of Endoscopy Videos |
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Conference Article |
Year |
2011 |
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Proceedings of the 8th IASTED International Conference on Biomedical Engineering |
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723 |
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800 |
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MV |
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no |
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fernando @ fernando @ |
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2426 |
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