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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 (up) 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 2408
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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 (up) 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 2421
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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 (up) 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 2425
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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 (up) 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 2484
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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 (up) 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 2505
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Author C. Alejandro Parraga
Title Color Vision, Computational Methods for Type Book Chapter
Year 2014 Publication Encyclopedia of Computational Neuroscience Abbreviated Journal
Volume Issue Pages 1-11
Keywords Color computational vision; Computational neuroscience of color
Abstract The study of color vision has been aided by a whole battery of computational methods that attempt to describe the mechanisms that lead to our perception of colors in terms of the information-processing properties of the visual system. Their scope is highly interdisciplinary, linking apparently dissimilar disciplines such as mathematics, physics, computer science, neuroscience, cognitive science, and psychology. Since the sensation of color is a feature of our brains, computational approaches usually include biological features of neural systems in their descriptions, from retinal light-receptor interaction to subcortical color opponency, cortical signal decoding, and color categorization. They produce hypotheses that are usually tested by behavioral or psychophysical experiments.
Address
Corporate Author Thesis
Publisher Springer-Verlag Berlin Heidelberg Place of Publication Editor Dieter Jaeger; Ranu Jung
Language Summary Language Original Title
Series Editor Series Title (up) Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-4614-7320-6 Medium
Area Expedition Conference
Notes CIC; 600.074 Approved no
Call Number Admin @ si @ Par2014 Serial 2512
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Author Svebor Karaman; Giuseppe Lisanti; Andrew Bagdanov; Alberto del Bimbo
Title From re-identification to identity inference: Labeling consistency by local similarity constraints Type Book Chapter
Year 2014 Publication Person Re-Identification Abbreviated Journal
Volume 2 Issue Pages 287-307
Keywords re-identification; Identity inference; Conditional random fields; Video surveillance
Abstract In this chapter, we introduce the problem of identity inference as a generalization of person re-identification. It is most appropriate to distinguish identity inference from re-identification in situations where a large number of observations must be identified without knowing a priori that groups of test images represent the same individual. The standard single- and multishot person re-identification common in the literature are special cases of our formulation. We present an approach to solving identity inference by modeling it as a labeling problem in a Conditional Random Field (CRF). The CRF model ensures that the final labeling gives similar labels to detections that are similar in feature space. Experimental results are given on the ETHZ, i-LIDS and CAVIAR datasets. Our approach yields state-of-the-art performance for multishot re-identification, and our results on the more general identity inference problem demonstrate that we are able to infer the identity of very many examples even with very few labeled images in the gallery.
Address
Corporate Author Thesis
Publisher Springer London Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title (up) Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2191-6586 ISBN 978-1-4471-6295-7 Medium
Area Expedition Conference
Notes LAMP; 600.079 Approved no
Call Number Admin @ si @KLB2014b Serial 2521
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Author Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez
Title Unsupervised and Notation-Independent Wall Segmentation in Floor Plans Using a Combination of Statistical and Structural Strategies Type Book Chapter
Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal
Volume 8746 Issue Pages 109-121
Keywords Graphics recognition; Floor plan analysis; Object segmentation
Abstract In this paper we present a wall segmentation approach in floor plans that is able to work independently to the graphical notation, does not need any pre-annotated data for learning, and is able to segment multiple-shaped walls such as beams and curved-walls. This method results from the combination of the wall segmentation approaches [3, 5] presented recently by the authors. Firstly, potential straight wall segments are extracted in an unsupervised way similar to [3], but restricting even more the wall candidates considered in the original approach. Then, based on [5], these segments are used to learn the texture pattern of walls and spot the lost instances. The presented combination of both methods has been tested on 4 available datasets with different notations and compared qualitatively and quantitatively to the state-of-the-art applied on these collections. Additionally, some qualitative results on floor plans directly downloaded from the Internet are reported in the paper. The overall performance of the method demonstrates either its adaptability to different wall notations and shapes, and to document qualities and resolutions.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title (up) Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium
Area Expedition Conference
Notes DAG; ADAS; 600.076; 600.077 Approved no
Call Number Admin @ si @ HVS2014 Serial 2535
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Author Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados
Title Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans Type Book Chapter
Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal
Volume 8746 Issue Pages 135-146
Keywords Graphics recognition; Graphics retrieval; Image classification
Abstract This paper proposes a runlength histogram signature as a perceptual descriptor of architectural plans in a retrieval scenario. The style of an architectural drawing is characterized by the perception of lines, shapes and texture. Such visual stimuli are the basis for defining semantic concepts as space properties, symmetry, density, etc. We propose runlength histograms extracted in vertical, horizontal and diagonal directions as a characterization of line and space properties in floorplans, so it can be roughly associated to a description of walls and room structure. A retrieval application illustrates the performance of the proposed approach, where given a plan as a query, similar ones are obtained from a database. A ground truth based on human observation has been constructed to validate the hypothesis. Additional retrieval results on sketched building’s facades are reported qualitatively in this paper. Its good description and its adaptability to two different sketch drawings despite its simplicity shows the interest of the proposed approach and opens a challenging research line in graphics recognition.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title (up) Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium
Area Expedition Conference
Notes DAG; ADAS; 600.045; 600.056; 600.061; 600.076; 600.077 Approved no
Call Number Admin @ si @ HFF2014 Serial 2536
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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.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor B.Lamiroy; J.-M. Ogier
Language Summary Language Original Title
Series Editor Series Title (up) 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 C. Alejandro Parraga
Title Perceptual Psychophysics Type Book Chapter
Year 2015 Publication Biologically-Inspired Computer Vision: Fundamentals and Applications Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor G.Cristobal; M.Keil; L.Perrinet
Language Summary Language Original Title
Series Editor Series Title (up) Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-3-527-41264-8 Medium
Area Expedition Conference
Notes CIC; 600.074 Approved no
Call Number Admin @ si @ Par2015 Serial 2600
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Author Jorge Bernal; F. Javier Sanchez; Cristina Rodriguez de Miguel; Gloria Fernandez Esparrach
Title Bulding up the future of colonoscopy: A synergy between clinicians and computer scientists Type Book Chapter
Year 2015 Publication Colonoscopy and Colorectal Cancer Abbreviated Journal
Volume Issue Pages
Keywords Intelligent systems; Image properties; Validation; Clinical drawbacks; Endoluminal scene description
Abstract Recent advances in endoscopic technology have generated an increasing interest in strengthening the collaboration between clinicians and computers scientist to develop intelligent systems that can provide additional information to clinicians in the different stages of an intervention. The objective of this chapter is to identify clinical drawbacks of colonoscopy in order to define potential areas of collaboration. Once areas are defined, we present the challenges that colonoscopy images present in order computational methods to provide with meaningful output, including those related to image formation and acquisition, as they are proven to have an impact in the performance of an intelligent system. Finally, we also propose how to define validation frameworks in order to assess the performance of a given method, making an special emphasis on how databases should be created and annotated and which metrics should be used to evaluate systems correctly.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title (up) Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-953-51-2225-8 Medium
Area Expedition Conference
Notes MV Approved no
Call Number Admin @ si @ BSR2015 Serial 2624
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Author Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados
Title Hierarchical Plausibility-Graphs for Symbol Spotting in Graphical Documents Type Book Chapter
Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal
Volume 8746 Issue Pages 25-37
Keywords
Abstract Graph representation of graphical documents often suffers from noise such as spurious nodes and edges, and their discontinuity. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance. But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result, the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor Bart Lamiroy; Jean-Marc Ogier
Language Summary Language Original Title
Series Editor Series Title (up) Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium
Area Expedition Conference
Notes DAG; 600.045; 600.056; 600.061; 600.077 Approved no
Call Number Admin @ si @ BDJ2014 Serial 2699
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Author Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados
Title Spotting Graphical Symbols in Camera-Acquired Documents in Real Time Type Book Chapter
Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal
Volume 8746 Issue Pages 3-10
Keywords
Abstract In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor Bart Lamiroy; Jean-Marc Ogier
Language Summary Language Original Title
Series Editor Series Title (up) Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium
Area Expedition Conference
Notes DAG; 600.045; 600.055; 600.061; 600.077 Approved no
Call Number Admin @ si @ RKL2014 Serial 2700
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Author Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados
Title Classification of Administrative Document Images by Logo Identification Type Book Chapter
Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal
Volume 8746 Issue Pages 49-58
Keywords Administrative Document Classification; Logo Recognition; Logo Spotting
Abstract This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier’s graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor Bart Lamiroy; Jean-Marc Ogier
Language Summary Language Original Title
Series Editor Series Title (up) Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium
Area Expedition Conference
Notes DAG; 600.056; 600.045; 605.203; 600.077 Approved no
Call Number Admin @ si @ RPK2014 Serial 2701
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