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Author Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu
Title Robust Head Gestures Recognition for Assistive Technology Type Book Chapter
Year 2014 Publication Pattern Recognition Abbreviated Journal
Volume 8495 Issue Pages 152-161
Keywords
Abstract This paper presents a system capable of recognizing six head gestures: nodding, shaking, turning right, turning left, looking up, and looking down. The main difference of our system compared to other methods is that the Hidden Markov Models presented in this paper, are fully connected and consider all possible states in any given order, providing the following advantages to the system: (1) allows unconstrained movement of the head and (2) it can be easily integrated into a wearable device (e.g. glasses, neck-hung devices), in which case it can robustly recognize gestures in the presence of ego-motion. Experimental results show that this approach outperforms common methods that use restricted HMMs for each gesture.
Address
Corporate Author Thesis
Publisher Springer International Publishing Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-319-07490-0 Medium
Area Expedition Conference
Notes LAMP; Approved no
Call Number Admin @ si @ TSR2014b Serial (down) 2505
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Author Salvatore Tabbone; Oriol Ramos Terrades
Title An Overview of Symbol Recognition Type Book Chapter
Year 2014 Publication Handbook of Document Image Processing and Recognition Abbreviated Journal
Volume D Issue Pages 523-551
Keywords Pattern recognition; Shape descriptors; Structural descriptors; Symbolrecognition; Symbol spotting
Abstract According to the Cambridge Dictionaries Online, a symbol is a sign, shape, or object that is used to represent something else. Symbol recognition is a subfield of general pattern recognition problems that focuses on identifying, detecting, and recognizing symbols in technical drawings, maps, or miscellaneous documents such as logos and musical scores. This chapter aims at providing the reader an overview of the different existing ways of describing and recognizing symbols and how the field has evolved to attain a certain degree of maturity.
Address
Corporate Author Thesis
Publisher Springer London Place of Publication Editor D. Doermann; K. Tombre
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-0-85729-858-4 Medium
Area Expedition Conference
Notes DAG; 600.077 Approved no
Call Number Admin @ si @ TaT2014 Serial (down) 2489
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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
Keywords
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.
Address
Corporate Author Thesis
Publisher Springer London Place of Publication Editor D. Doermann; K. Tombre
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-0-85729-860-7 Medium
Area Expedition Conference
Notes DAG; ADAS; 600.076; 600.077 Approved no
Call Number Admin @ si @ FoS2014 Serial (down) 2484
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Author A.Kesidis; Dimosthenis Karatzas
Title Logo and Trademark Recognition Type Book Chapter
Year 2014 Publication Handbook of Document Image Processing and Recognition Abbreviated Journal
Volume D Issue Pages 591-646
Keywords 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.
Address
Corporate Author Thesis
Publisher Springer London Place of Publication Editor D. Doermann; K. Tombre
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-0-85729-858-4 Medium
Area Expedition Conference
Notes DAG; 600.077 Approved no
Call Number Admin @ si @ KeK2014 Serial (down) 2425
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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 Type Book Chapter
Year 2013 Publication Graph Embedding for Pattern Analysis Abbreviated Journal
Volume Issue Pages 45-72
Keywords
Abstract 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.
Address
Corporate Author Thesis
Publisher Springer New York Place of Publication Editor Yun Fu; Yungian Ma
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-4614-4456-5 Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ FBV2013 Serial (down) 2421
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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
Volume 6020 Issue 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.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-13727-3 Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ RPL2010c Serial (down) 2408
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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
Volume 6020 Issue Pages 187-198
Keywords
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.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-13727-3 Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ RBO2010 Serial (down) 2407
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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 Abbreviated Journal
Volume 6020 Issue Pages 260–271
Keywords
Abstract 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).
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-13727-3 Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number Admin @ si @ DRV2010 Serial (down) 2406
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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 Abbreviated Journal
Volume 6020 Issue Pages 118-129
Keywords
Abstract 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.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-13727-3 Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number MSL2010 Serial (down) 2405
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Author Salim Jouili; Salvatore Tabbone; Ernest Valveny
Title Comparing Graph Similarity Measures for Graphical Recognition Type Book Chapter
Year 2010 Publication Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers Abbreviated Journal
Volume 6020 Issue Pages 37-48
Keywords
Abstract In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used including line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each graph distance measure depends on the kind of data and the graph representation technique.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-13727-3 Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number Admin @ si @ JTV2010 Serial (down) 2404
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Author Josep Llados; Marçal Rusiñol
Title Graphics Recognition Techniques Type Book Chapter
Year 2014 Publication Handbook of Document Image Processing and Recognition Abbreviated Journal
Volume D Issue Pages 489-521
Keywords Dimension recognition; Graphics recognition; Graphic-rich documents; Polygonal approximation; Raster-to-vector conversion; Texture-based primitive extraction; Text-graphics separation
Abstract This chapter describes the most relevant approaches for the analysis of graphical documents. The graphics recognition pipeline can be splitted into three tasks. The low level or lexical task extracts the basic units composing the document. The syntactic level is focused on the structure, i.e., how graphical entities are constructed, and involves the location and classification of the symbols present in the document. The third level is a functional or semantic level, i.e., it models what the graphical symbols do and what they mean in the context where they appear. This chapter covers the lexical level, while the next two chapters are devoted to the syntactic and semantic level, respectively. The main problems reviewed in this chapter are raster-to-vector conversion (vectorization algorithms) and the separation of text and graphics components. The research and industrial communities have provided standard methods achieving reasonable performance levels. Hence, graphics recognition techniques can be considered to be in a mature state from a scientific point of view. Additionally this chapter provides insights on some related problems, namely, the extraction and recognition of dimensions in engineering drawings, and the recognition of hatched and tiled patterns. Both problems are usually associated, even integrated, in the vectorization process.
Address
Corporate Author Thesis
Publisher Springer London Place of Publication Editor D. Doermann; K. Tombre
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-0-85729-858-4 Medium
Area Expedition Conference
Notes DAG; 600.077 Approved no
Call Number Admin @ si @ LlR2014 Serial (down) 2380
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Author Ernest Valveny; Oriol Ramos Terrades; Joan Mas; Marçal Rusiñol
Title Interactive Document Retrieval and Classification. Type Book Chapter
Year 2013 Publication Multimodal Interaction in Image and Video Applications Abbreviated Journal
Volume 48 Issue Pages 17-30
Keywords
Abstract In this chapter we describe a system for document retrieval and classification following the interactive-predictive framework. In particular, the system addresses two different scenarios of document analysis: document classification based on visual appearance and logo detection. These two classical problems of document analysis are formulated following the interactive-predictive model, taking the user interaction into account to make easier the process of annotating and labelling the documents. A system implementing this model in a real scenario is presented and analyzed. This system also takes advantage of active learning techniques to speed up the task of labelling the documents.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor Angel Sappa; Jordi Vitria
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ VRM2013 Serial (down) 2341
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Author Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny
Title Notation-invariant patch-based wall detector in architectural floor plans Type Book Chapter
Year 2013 Publication Graphics Recognition. New Trends and Challenges Abbreviated Journal
Volume 7423 Issue Pages 79--88
Keywords
Abstract Architectural floor plans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. This paper presents an evolution of that previous work, after analyzing and testing several alternatives for each of the different steps of the method: Firstly, an automatic plan-size normalization process is done. Secondly we evaluate different features to obtain the description of every patch. Thirdly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These variations of the method have been tested for wall detection on two datasets of architectural floor plans with different notations. After studying in deep each of the steps in the process pipeline, we are able to find the best system configuration, which highly outperforms the results on wall segmentation obtained by the original paper.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-36823-3 Medium
Area Expedition Conference
Notes DAG; 600.045; 600.056; 605.203 Approved no
Call Number Admin @ si @ HMS2013 Serial (down) 2322
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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
Volume 8 Issue Pages 87-99
Keywords
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.
Address
Corporate Author Thesis
Publisher Springer Netherlands Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2212-9391 ISBN 978-94-007-0725-2 Medium
Area Expedition Conference
Notes ISE; 605.203; 302.018; 600.049 Approved no
Call Number Admin @ si @ FGT2013 Serial (down) 2287
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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
Volume 48 Issue Pages 31-35
Keywords
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.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor Angel Sappa; Jordi Vitria
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium
Area Expedition Conference
Notes CIC; 605.203; 600.048 Approved no
Call Number Admin @ si @ WKC2013 Serial (down) 2284
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