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Author Anjan Dutta; Pau Riba; Josep Llados; Alicia Fornes
Title Pyramidal Stochastic Graphlet Embedding for Document Pattern Classification Type Conference Article
Year 2017 Publication 14th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages (down) 33-38
Keywords graph embedding; hierarchical graph representation; graph clustering; stochastic graphlet embedding; graph classification
Abstract Document pattern classification methods using graphs have received a lot of attention because of its robust representation paradigm and rich theoretical background. However, the way of preserving and the process for delineating documents with graphs introduce noise in the rendition of underlying data, which creates instability in the graph representation. To deal with such unreliability in representation, in this paper, we propose Pyramidal Stochastic Graphlet Embedding (PSGE).
Given a graph representing a document pattern, our method first computes a graph pyramid by successively reducing the base graph. Once the graph pyramid is computed, we apply Stochastic Graphlet Embedding (SGE) for each level of the pyramid and combine their embedded representation to obtain a global delineation of the original graph. The consideration of pyramid of graphs rather than just a base graph extends the representational power of the graph embedding, which reduces the instability caused due to noise and distortion. When plugged with support
vector machine, our proposed PSGE has outperformed the state-of-the-art results in recognition of handwritten words as well as graphical symbols
Address
Corporate Author 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 Medium
Area Expedition Conference ICDAR
Notes DAG; 600.097; 601.302; 600.121 Approved no
Call Number Admin @ si @ DRL2017 Serial 3054
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Author Fadi Dornaika; Bogdan Raducanu
Title Single Snapshot 3D Head Pose Initialization for Tracking in Human Robot Interaction Scenario Type Conference Article
Year 2010 Publication 1st International Workshop on Computer Vision for Human-Robot Interaction Abbreviated Journal
Volume Issue Pages (down) 32–39
Keywords 1st International Workshop on Computer Vision for Human-Robot Interaction, in conjunction with IEEE CVPR 2010
Abstract This paper presents an automatic 3D head pose initialization scheme for a real-time face tracker with application to human-robot interaction. It has two main contributions. First, we propose an automatic 3D head pose and person specific face shape estimation, based on a 3D deformable model. The proposed approach serves to initialize our realtime 3D face tracker. What makes this contribution very attractive is that the initialization step can cope with faces
under arbitrary pose, so it is not limited only to near-frontal views. Second, the previous framework is used to develop an application in which the orientation of an AIBO’s camera can be controlled through the imitation of user’s head pose.
In our scenario, this application is used to build panoramic images from overlapping snapshots. Experiments on real videos confirm the robustness and usefulness of the proposed methods.
Address San Francisco; CA; USA; June 2010
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2160-7508 ISBN 978-1-4244-7029-7 Medium
Area Expedition Conference CVPRW
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ DoR2010a Serial 1309
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Author Yael Tudela; Ana Garcia Rodriguez; Gloria Fernandez Esparrach; Jorge Bernal
Title Towards Fine-Grained Polyp Segmentation and Classification Type Conference Article
Year 2023 Publication Workshop on Clinical Image-Based Procedures Abbreviated Journal
Volume 14242 Issue Pages (down) 32-42
Keywords Medical image segmentation; Colorectal Cancer; Vision Transformer; Classification
Abstract Colorectal cancer is one of the main causes of cancer death worldwide. Colonoscopy is the gold standard screening tool as it allows lesion detection and removal during the same procedure. During the last decades, several efforts have been made to develop CAD systems to assist clinicians in lesion detection and classification. Regarding the latter, and in order to be used in the exploration room as part of resect and discard or leave-in-situ strategies, these systems must identify correctly all different lesion types. This is a challenging task, as the data used to train these systems presents great inter-class similarity, high class imbalance, and low representation of clinically relevant histology classes such as serrated sessile adenomas.

In this paper, a new polyp segmentation and classification method, Swin-Expand, is introduced. Based on Swin-Transformer, it uses a simple and lightweight decoder. The performance of this method has been assessed on a novel dataset, comprising 1126 high-definition images representing the three main histological classes. Results show a clear improvement in both segmentation and classification performance, also achieving competitive results when tested in public datasets. These results confirm that both the method and the data are important to obtain more accurate polyp representations.
Address Vancouver; October 2023
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference MICCAIW
Notes ISE Approved no
Call Number Admin @ si @ TGF2023 Serial 3837
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Author Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez
Title On-line lumen centre detection in gastrointestinal and respiratory endoscopy Type Conference Article
Year 2013 Publication Second International Workshop Clinical Image-Based Procedures Abbreviated Journal
Volume 8361 Issue Pages (down) 31-38
Keywords Lumen centre detection; Bronchoscopy; Colonoscopy
Abstract We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %).
Address Nagoya; Japan; September 2013
Corporate Author Thesis
Publisher Springer International Publishing Place of Publication Editor Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-319-05665-4 Medium
Area 800 Expedition Conference CLIP
Notes MV; IAM; 600.047; 600.044; 600.060 Approved no
Call Number Admin @ si @ SBG2013 Serial 2302
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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 (down) 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 2284
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Author Sounak Dey; Anjan Dutta; Josep Llados; Alicia Fornes; Umapada Pal
Title Shallow Neural Network Model for Hand-drawn Symbol Recognition in Multi-Writer Scenario Type Conference Article
Year 2017 Publication 12th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages (down) 31-32
Keywords
Abstract One of the main challenges in hand drawn symbol recognition is the variability among symbols because of the different writer styles. In this paper, we present and discuss some results recognizing hand-drawn symbols with a shallow neural network. A neural network model inspired from the LeNet architecture has been used to achieve state-of-the-art results with
very less training data, which is very unlikely to the data hungry deep neural network. From the results, it has become evident that the neural network architectures can efficiently describe and recognize hand drawn symbols from different writers and can model the inter author aberration
Address
Corporate Author 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 Medium
Area Expedition Conference GREC
Notes DAG; 600.097; 600.121 Approved no
Call Number Admin @ si @ DDL2017 Serial 3057
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Author Christian Keilstrup Ingwersen; Artur Xarles; Albert Clapes; Meysam Madadi; Janus Nortoft Jensen; Morten Rieger Hannemose; Anders Bjorholm Dahl; Sergio Escalera
Title Video-based Skill Assessment for Golf: Estimating Golf Handicap Type Conference Article
Year 2023 Publication Proceedings of the 6th International Workshop on Multimedia Content Analysis in Sports Abbreviated Journal
Volume Issue Pages (down) 31-39
Keywords
Abstract Automated skill assessment in sports using video-based analysis holds great potential for revolutionizing coaching methodologies. This paper focuses on the problem of skill determination in golfers by leveraging deep learning models applied to a large database of video recordings of golf swings. We investigate different regression, ranking and classification based methods and compare to a simple baseline approach. The performance is evaluated using mean squared error (MSE) as well as computing the percentages of correctly ranked pairs based on the Kendall correlation. Our results demonstrate an improvement over the baseline, with a 35% lower mean squared error and 68% correctly ranked pairs. However, achieving fine-grained skill assessment remains challenging. This work contributes to the development of AI-driven coaching systems and advances the understanding of video-based skill determination in the context of golf.
Address Otawa; Canada; October 2023
Corporate Author 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 Medium
Area Expedition Conference MMSports
Notes HUPBA Approved no
Call Number Admin @ si @ KXC2023 Serial 3929
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Author Partha Pratim Roy; Josep Llados
Title Multi-Oriented Character Recognition from Graphical Documents Type Conference Article
Year 2008 Publication 2nd International Conference on Cognition and Recognition Abbreviated Journal
Volume Issue Pages (down) 30–35
Keywords
Abstract
Address Mandya (India)
Corporate Author 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 Medium
Area Expedition Conference ICCR
Notes DAG Approved no
Call Number DAG @ dag @ RLP2008 Serial 965
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Author Alicia Fornes; Sergio Escalera; Josep Llados; Gemma Sanchez; Joan Mas
Title Hand Drawn Symbol Recognition by Blurred Shape Model Descriptor and a Multiclass Classifier Type Book Chapter
Year 2008 Publication Graphics Recognition: Recent Advances and New Opportunities Abbreviated Journal
Volume 5046 Issue Pages (down) 30–40
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor W. Liu, J. Llados, J.M. Ogier
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes DAG; HUPBA; MILAB Approved no
Call Number BCNPCL @ bcnpcl @ FEL2008 Serial 989
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Author Cesar Isaza; Joaquin Salas; Bogdan Raducanu
Title Toward the Detection of Urban Infrastructures Edge Shadows Type Conference Article
Year 2010 Publication 12th International Conference on Advanced Concepts for Intelligent Vision Systems Abbreviated Journal
Volume 6474 Issue I Pages (down) 30–37
Keywords
Abstract In this paper, we propose a novel technique to detect the shadows cast by urban infrastructure, such as buildings, billboards, and traffic signs, using a sequence of images taken from a fixed camera. In our approach, we compute two different background models in parallel: one for the edges and one for the reflected light intensity. An algorithm is proposed to train the system to distinguish between moving edges in general and edges that belong to static objects, creating an edge background model. Then, during operation, a background intensity model allow us to separate between moving and static objects. Those edges included in the moving objects and those that belong to the edge background model are subtracted from the current image edges. The remaining edges are the ones cast by urban infrastructure. Our method is tested on a typical crossroad scene and the results show that the approach is sound and promising.
Address Sydney, Australia
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor eds. Blanc–Talon et al
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-17687-6 Medium
Area Expedition Conference ACIVS
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ ISR2010 Serial 1458
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Author Jaume Gibert; Ernest Valveny; Horst Bunke
Title Graph of Words Embedding for Molecular Structure-Activity Relationship Analysis Type Conference Article
Year 2010 Publication 15th Iberoamerican Congress on Pattern Recognition Abbreviated Journal
Volume 6419 Issue Pages (down) 30–37
Keywords
Abstract Structure-Activity relationship analysis aims at discovering chemical activity of molecular compounds based on their structure. In this article we make use of a particular graph representation of molecules and propose a new graph embedding procedure to solve the problem of structure-activity relationship analysis. The embedding is essentially an arrangement of a molecule in the form of a vector by considering frequencies of appearing atoms and frequencies of covalent bonds between them. Results on two benchmark databases show the effectiveness of the proposed technique in terms of recognition accuracy while avoiding high operational costs in the transformation.
Address Sao Paulo, Brazil
Corporate Author Thesis
Publisher 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 978-3-642-16686-0 Medium
Area Expedition Conference CIARP
Notes DAG Approved no
Call Number DAG @ dag @ GVB2010 Serial 1462
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Author Jaume Garcia; Joel Barajas; Francesc Carreras; Sandra Pujades; Petia Radeva
Title An intuitive validation technique to compare local versus global tagged MRI analysis Type Conference Article
Year 2005 Publication Computers In Cardiology Abbreviated Journal
Volume 32 Issue Pages (down) 29–32
Keywords
Abstract Myocardium appears as a uniform tissue that seen in convectional Magnetic Resonance Images (MRI) shows just the contractile part of its movement. MR Tagging is a unique imaging technique that prints a grid over the tissue which moves according to the underlying movement of the myocardium revealing the true deformation of the cardiac muscle. Optical flow techniques based on spectral information estimate tissue displacement by analyzing information encoded in the phase maps which can be obtained using, local (Gabor) and global (HARP) methods. In this paper we compare both in synthetic and real Tagged MR sequences. We conclude that local method is slightly more accurate than the global one. On the other hand, global method is more efficient as it is much faster and less parameters have to be taken into account
Address Lyon (France)
Corporate Author 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 0-7803-9337-6 Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GBC2005 Serial 639
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Author Ferran Poveda; Jaume Garcia; Enric Marti; Debora Gil
Title Validation of the myocardial architecture in DT-MRI tractography Type Conference Article
Year 2010 Publication Medical Image Computing in Catalunya: Graduate Student Workshop Abbreviated Journal
Volume Issue Pages (down) 29-30
Keywords
Abstract Deep understanding of myocardial structure may help to link form and funcion of the heart unraveling crucial knowledge for medical and surgical clinical procedures and studies. In this work we introduce two visualization techniques based on DT-MRI streamlining able to decipher interesting properties of the architectural organization of the heart.
Address
Corporate Author Thesis
Publisher Place of Publication Girona (Spain) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference MICCAT
Notes IAM Approved no
Call Number IAM @ iam @ PGM2010 Serial 1626
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Author Andreas Fischer; Volkmar Frinken; Alicia Fornes; Horst Bunke
Title Transcription Alignment of Latin Manuscripts Using Hidden Markov Models Type Conference Article
Year 2011 Publication Proceedings of the 2011 Workshop on Historical Document Imaging and Processing Abbreviated Journal
Volume Issue Pages (down) 29-36
Keywords
Abstract Transcriptions of historical documents are a valuable source for extracting labeled handwriting images that can be used for training recognition systems. In this paper, we introduce the Saint Gall database that includes images as well as the transcription of a Latin manuscript from the 9th century written in Carolingian script. Although the available transcription is of high quality for a human reader, the spelling of the words is not accurate when compared with the handwriting image. Hence, the transcription poses several challenges for alignment regarding, e.g., line breaks, abbreviations, and capitalization. We propose an alignment system based on character Hidden Markov Models that can cope with these challenges and efficiently aligns complete document pages. On the Saint Gall database, we demonstrate that a considerable alignment accuracy can be achieved, even with weakly trained character models.
Address
Corporate Author Thesis
Publisher ACM Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference HIP
Notes DAG Approved no
Call Number Admin @ si @ FFF2011b Serial 1824
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Author Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
Title Three-Dimensional Design of Error Correcting Output Codes Type Conference Article
Year 2012 Publication 8th International Conference on Machine Learning and Data Mining Abbreviated Journal
Volume Issue Pages (down) 29-
Keywords
Abstract
Address Berlin, Germany
Corporate Author 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 Medium
Area Expedition Conference MLDM
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ BGE2012a Serial 2041
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