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Author Tadashi Araki; Sumit K. Banchhor; Narendra D. Londhe; Nobutaka Ikeda; Petia Radeva; Devarshi Shukla; Luca Saba; Antonella Balestrieri; Andrew Nicolaides; Shoaib Shafique; John R. Laird; Jasjit S. Suri edit  doi
openurl 
  Title Reliable and Accurate Calcium Volume Measurement in Coronary Artery Using Intravascular Ultrasound Videos Type Journal Article
  Year 2016 Publication Journal of Medical Systems Abbreviated Journal JMS  
  Volume 40 Issue 3 Pages 51:1-51:20  
  Keywords Interventional cardiology; Atherosclerosis; Coronary arteries; IVUS; calcium volume; Soft computing; Performance Reliability; Accuracy  
  Abstract Quantitative assessment of calcified atherosclerotic volume within the coronary artery wall is vital for cardiac interventional procedures. The goal of this study is to automatically measure the calcium volume, given the borders of coronary vessel wall for all the frames of the intravascular ultrasound (IVUS) video. Three soft computing fuzzy classification techniques were adapted namely Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF) for automated segmentation of calcium regions and volume computation. These methods were benchmarked against previously developed threshold-based method. IVUS image data sets (around 30,600 IVUS frames) from 15 patients were collected using 40 MHz IVUS catheter (Atlantis® SR Pro, Boston Scientific®, pullback speed of 0.5 mm/s). Calcium mean volume for FCM, K-means, HMRF and threshold-based method were 37.84 ± 17.38 mm3, 27.79 ± 10.94 mm3, 46.44 ± 19.13 mm3 and 35.92 ± 16.44 mm3 respectively. Cross-correlation, Jaccard Index and Dice Similarity were highest between FCM and threshold-based method: 0.99, 0.92 ± 0.02 and 0.95 + 0.02 respectively. Student’s t-test, z-test and Wilcoxon-test are also performed to demonstrate consistency, reliability and accuracy of the results. Given the vessel wall region, the system reliably and automatically measures the calcium volume in IVUS videos. Further, we validated our system against a trained expert using scoring: K-means showed the best performance with an accuracy of 92.80 %. Out procedure and protocol is along the line with method previously published clinically.  
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  Notes MILAB; Approved no  
  Call Number Admin @ si @ ABL2016 Serial 2729  
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Author Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados edit  openurl
  Title Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans Type Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Bethlehem; PA; USA; August 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference GREC  
  Notes DAG; 600.045; 600.061; 600.056 Approved no  
  Call Number Admin @ si @ HFF2013b Serial 2695  
Permanent link to this record
 

 
Author Mikhail Mozerov; Joost Van de Weijer edit  doi
openurl 
  Title Global Color Sparseness and a Local Statistics Prior for Fast Bilateral Filtering Type Journal Article
  Year 2015 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP  
  Volume 24 Issue 12 Pages 5842-5853  
  Keywords  
  Abstract The property of smoothing while preserving edges makes the bilateral filter a very popular image processing tool. However, its non-linear nature results in a computationally costly operation. Various works propose fast approximations to the bilateral filter. However, the majority does not generalize to vector input as is the case with color images. We propose a fast approximation to the bilateral filter for color images. The filter is based on two ideas. First, the number of colors, which occur in a single natural image, is limited. We exploit this color sparseness to rewrite the initial non-linear bilateral filter as a number of linear filter operations. Second, we impose a statistical prior to the image values that are locally present within the filter window. We show that this statistical prior leads to a closed-form solution of the bilateral filter. Finally, we combine both ideas into a single fast and accurate bilateral filter for color images. Experimental results show that our bilateral filter based on the local prior yields an extremely fast bilateral filter approximation, but with limited accuracy, which has potential application in real-time video filtering. Our bilateral filter, which combines color sparseness and local statistics, yields a fast and accurate bilateral filter approximation and obtains the state-of-the-art results.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume (down) Series Issue Edition  
  ISSN 1057-7149 ISBN Medium  
  Area Expedition Conference  
  Notes LAMP; 600.079;ISE Approved no  
  Call Number Admin @ si @ MoW2015b Serial 2689  
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Author Dimosthenis Karatzas; Lluis Gomez; A.Nicolaou ; Suman Ghosh; Andrew Bagdanov; Masakazu Iwamura; J.Matas; L.Neumann; V.Ramaseshan; S.Lu ; Faisal Shafait; Seiichi Uchida; Ernest Valveny edit  doi
openurl 
  Title ICDAR 2015 Competition on Robust Reading Type Conference Article
  Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal  
  Volume Issue Pages 1156-1160  
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  ISSN ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; 600.077; 600.084 Approved no  
  Call Number Admin @ si @ KGN2015 Serial 2690  
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Author Lluis Gomez; Dimosthenis Karatzas edit   pdf
url  doi
openurl 
  Title Object Proposals for Text Extraction in the Wild Type Conference Article
  Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal  
  Volume Issue Pages 206 - 210  
  Keywords  
  Abstract Object Proposals is a recent computer vision technique receiving increasing interest from the research community. Its main objective is to generate a relatively small set of bounding box proposals that are most likely to contain objects of interest. The use of Object Proposals techniques in the scene text understanding field is innovative. Motivated by the success of powerful while expensive techniques to recognize words in a holistic way, Object Proposals techniques emerge as an alternative to the traditional text detectors. In this paper we study to what extent the existing generic Object Proposals methods may be useful for scene text understanding. Also, we propose a new Object Proposals algorithm that is specifically designed for text and compare it with other generic methods in the state of the art. Experiments show that our proposal is superior in its ability of producing good quality word proposals in an efficient way. The source code of our method is made publicly available  
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  ISSN ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; 600.077; 600.084; 601.197 Approved no  
  Call Number Admin @ si @ GoK2015 Serial 2691  
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Author A.Nicolaou; Andrew Bagdanov; Marcus Liwicki; Dimosthenis Karatzas edit   pdf
url  openurl
  Title Sparse Radial Sampling LBP for Writer Identification Type Conference Article
  Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal  
  Volume Issue Pages 716-720  
  Keywords  
  Abstract In this paper we present the use of Sparse Radial Sampling Local Binary Patterns, a variant of Local Binary Patterns (LBP) for text-as-texture classification. By adapting and extending the standard LBP operator to the particularities of text we get a generic text-as-texture classification scheme and apply it to writer identification. In experiments on CVL and ICDAR 2013 datasets, the proposed feature-set demonstrates State-Of-the-Art (SOA) performance. Among the SOA, the proposed method is the only one that is based on dense extraction of a single local feature descriptor. This makes it fast and applicable at the earliest stages in a DIA pipeline without the need for segmentation, binarization, or extraction of multiple features.  
  Address Nancy; France; August 2015  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume (down) Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ NBL2015 Serial 2692  
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Author Suman Ghosh; Lluis Gomez; Dimosthenis Karatzas; Ernest Valveny edit   pdf
doi  openurl
  Title Efficient indexing for Query By String text retrieval Type Conference Article
  Year 2015 Publication 6th IAPR International Workshop on Camera Based Document Analysis and Recognition CBDAR2015 Abbreviated Journal  
  Volume Issue Pages 1236 - 1240  
  Keywords  
  Abstract This paper deals with Query By String word spotting in scene images. A hierarchical text segmentation algorithm based on text specific selective search is used to find text regions. These regions are indexed per character n-grams present in the text region. An attribute representation based on Pyramidal Histogram of Characters (PHOC) is used to compare text regions with the query text. For generation of the index a similar attribute space based Pyramidal Histogram of character n-grams is used. These attribute models are learned using linear SVMs over the Fisher Vector [1] representation of the images along with the PHOC labels of the corresponding strings.  
  Address Nancy; France; August 2015  
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  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume (down) Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CBDAR  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ GGK2015 Serial 2693  
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Author J.Kuhn; A.Nussbaumer; J.Pirker; Dimosthenis Karatzas; A. Pagani; O.Conlan; M.Memmel; C.M.Steiner; C.Gutl; D.Albert; Andreas Dengel edit  url
doi  openurl
  Title Advancing Physics Learning Through Traversing a Multi-Modal Experimentation Space Type Conference Article
  Year 2015 Publication Workshop Proceedings on the 11th International Conference on Intelligent Environments Abbreviated Journal  
  Volume 19 Issue Pages 373-380  
  Keywords  
  Abstract Translating conceptual knowledge into real world experiences presents a significant educational challenge. This position paper presents an approach that supports learners in moving seamlessly between conceptual learning and their application in the real world by bringing physical and virtual experiments into everyday settings. Learners are empowered in conducting these situated experiments in a variety of physical settings by leveraging state of the art mobile, augmented reality, and virtual reality technology. A blend of mobile-based multi-sensory physical experiments, augmented reality and enabling virtual environments can allow learners to bridge their conceptual learning with tangible experiences in a completely novel manner. This approach focuses on the learner by applying self-regulated personalised learning techniques, underpinned by innovative pedagogical approaches and adaptation techniques, to ensure that the needs and preferences of each learner are catered for individually.  
  Address Praga; Chzech Republic; July 2015  
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  ISSN ISBN Medium  
  Area Expedition Conference IE  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ KNP2015 Serial 2694  
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Author Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez edit  openurl
  Title Unsupervised and Notation-Independent Wall Segmentation in Floor Plans Using a Combination of Statistical and Structural Strategies Type Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Bethlehem; PA; USA; August 2013  
  Corporate Author Thesis  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume (down) Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GREC  
  Notes DAG Approved no  
  Call Number Admin @ si @ HVS2013b Serial 2696  
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Author Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados edit   pdf
doi  isbn
openurl 
  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 Abbreviated Series Title LNCS  
  Series Volume (down) 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 edit  doi
isbn  openurl
  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  
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  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 Abbreviated Series Title LNCS  
  Series Volume (down) 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 edit   pdf
doi  isbn
openurl 
  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 Abbreviated Series Title  
  Series Volume (down) 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  
Permanent link to this record
 

 
Author Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva edit  doi
openurl 
  Title Towards social interaction detection in egocentric photo-streams Type Conference Article
  Year 2015 Publication Proceedings of SPIE, 8th International Conference on Machine Vision , ICMV 2015 Abbreviated Journal  
  Volume 9875 Issue Pages  
  Keywords  
  Abstract Detecting social interaction in videos relying solely on visual cues is a valuable task that is receiving increasing attention in recent years. In this work, we address this problem in the challenging domain of egocentric photo-streams captured by a low temporal resolution wearable camera (2fpm). The major difficulties to be handled in this context are the sparsity of observations as well as unpredictability of camera motion and attention orientation due to the fact that the camera is worn as part of clothing. Our method consists of four steps: multi-faces localization and tracking, 3D localization, pose estimation and analysis of f-formations. By estimating pair-to-pair interaction probabilities over the sequence, our method states the presence or absence of interaction with the camera wearer and specifies which people are more involved in the interaction. We tested our method over a dataset of 18.000 images and we show its reliability on our considered purpose. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.  
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  Area Expedition Conference ICMV  
  Notes MILAB Approved no  
  Call Number Admin @ si @ ADR2015a Serial 2702  
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Author Ivan Huerta; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez edit   pdf
doi  openurl
  Title Chromatic shadow detection and tracking for moving foreground segmentation Type Journal Article
  Year 2015 Publication Image and Vision Computing Abbreviated Journal IMAVIS  
  Volume 41 Issue Pages 42-53  
  Keywords Detecting moving objects; Chromatic shadow detection; Temporal local gradient; Spatial and Temporal brightness and angle distortions; Shadow tracking  
  Abstract Advanced segmentation techniques in the surveillance domain deal with shadows to avoid distortions when detecting moving objects. Most approaches for shadow detection are still typically restricted to penumbra shadows and cannot cope well with umbra shadows. Consequently, umbra shadow regions are usually detected as part of moving objects, thus a ecting the performance of the nal detection. In this paper we address the detection of both penumbra and umbra shadow regions. First, a novel bottom-up approach is presented based on gradient and colour models, which successfully discriminates between chromatic moving cast shadow regions and those regions detected as moving objects. In essence, those regions corresponding to potential shadows are detected based on edge partitioning and colour statistics. Subsequently (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for each potential shadow region for detecting the umbra shadow regions. Our second contribution re nes even further the segmentation results: a tracking-based top-down approach increases the performance of our bottom-up chromatic shadow detection algorithm by properly correcting non-detected shadows.
To do so, a combination of motion lters in a data association framework exploits the temporal consistency between objects and shadows to increase
the shadow detection rate. Experimental results exceed current state-of-the-
art in shadow accuracy for multiple well-known surveillance image databases which contain di erent shadowed materials and illumination conditions.
 
  Address  
  Corporate Author Thesis  
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  Series Editor Series Title Abbreviated Series Title  
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  Notes ISE; 600.078; 600.063 Approved no  
  Call Number Admin @ si @ HHM2015 Serial 2703  
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Author Sergio Escalera; Junior Fabian; Pablo Pardo; Xavier Baro; Jordi Gonzalez; Hugo Jair Escalante; Marc Oliu; Dusan Misevic; Ulrich Steiner; Isabelle Guyon edit   pdf
url  doi
openurl 
  Title ChaLearn Looking at People 2015: Apparent Age and Cultural Event Recognition Datasets and Results Type Conference Article
  Year 2015 Publication 16th IEEE International Conference on Computer Vision Workshops Abbreviated Journal  
  Volume Issue Pages 243 - 251  
  Keywords  
  Abstract Following previous series on Looking at People (LAP) competitions [14, 13, 11, 12, 2], in 2015 ChaLearn ran two new competitions within the field of Looking at People: (1) age estimation, and (2) cultural event recognition, both in
still images. We developed a crowd-sourcing application to collect and label data about the apparent age of people (as opposed to the real age). In terms of cultural event recognition, one hundred categories had to be recognized. These
tasks involved scene understanding and human body analysis. This paper summarizes both challenges and data, as well as the results achieved by the participants of the competition.
 
  Address Santiago de Chile; December 2015  
  Corporate Author Thesis  
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  ISSN ISBN Medium  
  Area Expedition Conference ICCVW  
  Notes ISE; 600.063; 600.078;MV Approved no  
  Call Number Admin @ si @ EFP2015 Serial 2704  
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