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Author | Carolina Malagelada; Michal Drozdzal; Santiago Segui; Sara Mendez; Jordi Vitria; Petia Radeva; Javier Santos; Anna Accarino; Juan R. Malagelada; Fernando Azpiroz | ||||
Title | Classification of functional bowel disorders by objective physiological criteria based on endoluminal image analysis | Type | Journal Article | ||
Year | 2015 | Publication | American Journal of Physiology-Gastrointestinal and Liver Physiology | Abbreviated Journal | AJPGI |
Volume | 309 | Issue | 6 | Pages | G413--G419 |
Keywords | capsule endoscopy; computer vision analysis; functional bowel disorders; intestinal motility; machine learning | ||||
Abstract | We have previously developed an original method to evaluate small bowel motor function based on computer vision analysis of endoluminal images obtained by capsule endoscopy. Our aim was to demonstrate intestinal motor abnormalities in patients with functional bowel disorders by endoluminal vision analysis. Patients with functional bowel disorders (n = 205) and healthy subjects (n = 136) ingested the endoscopic capsule (Pillcam-SB2, Given-Imaging) after overnight fast and 45 min after gastric exit of the capsule a liquid meal (300 ml, 1 kcal/ml) was administered. Endoluminal image analysis was performed by computer vision and machine learning techniques to define the normal range and to identify clusters of abnormal function. After training the algorithm, we used 196 patients and 48 healthy subjects, completely naive, as test set. In the test set, 51 patients (26%) were detected outside the normal range (P < 0.001 vs. 3 healthy subjects) and clustered into hypo- and hyperdynamic subgroups compared with healthy subjects. Patients with hypodynamic behavior (n = 38) exhibited less luminal closure sequences (41 ± 2% of the recording time vs. 61 ± 2%; P < 0.001) and more static sequences (38 ± 3 vs. 20 ± 2%; P < 0.001); in contrast, patients with hyperdynamic behavior (n = 13) had an increased proportion of luminal closure sequences (73 ± 4 vs. 61 ± 2%; P = 0.029) and more high-motion sequences (3 ± 1 vs. 0.5 ± 0.1%; P < 0.001). Applying an original methodology, we have developed a novel classification of functional gut disorders based on objective, physiological criteria of small bowel function. | ||||
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Publisher | American Physiological Society | Place of Publication | Editor | ||
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Notes | MILAB; OR;MV | Approved | no | ||
Call Number | Admin @ si @ MDS2015 | Serial | 2666 | ||
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Author | R.A.Bendezu; E.Barba; E.Burri; D.Cisternas; Carolina Malagelada; Santiago Segui; Anna Accarino; S.Quiroga; E.Monclus; I.Navazo | ||||
Title | Intestinal gas content and distribution in health and in patients with functional gut symptoms | Type | Journal Article | ||
Year | 2015 | Publication | Neurogastroenterology & Motility | Abbreviated Journal | NEUMOT |
Volume | 27 | Issue | 9 | Pages | 1249-1257 |
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Abstract | BACKGROUND:
The precise relation of intestinal gas to symptoms, particularly abdominal bloating and distension remains incompletely elucidated. Our aim was to define the normal values of intestinal gas volume and distribution and to identify abnormalities in relation to functional-type symptoms. METHODS: Abdominal computed tomography scans were evaluated in healthy subjects (n = 37) and in patients in three conditions: basal (when they were feeling well; n = 88), during an episode of abdominal distension (n = 82) and after a challenge diet (n = 24). Intestinal gas content and distribution were measured by an original analysis program. Identification of patients outside the normal range was performed by machine learning techniques (one-class classifier). Results are expressed as median (IQR) or mean ± SE, as appropriate. KEY RESULTS: In healthy subjects the gut contained 95 (71, 141) mL gas distributed along the entire lumen. No differences were detected between patients studied under asymptomatic basal conditions and healthy subjects. However, either during a spontaneous bloating episode or once challenged with a flatulogenic diet, luminal gas was found to be increased and/or abnormally distributed in about one-fourth of the patients. These patients detected outside the normal range by the classifier exhibited a significantly greater number of abnormal features than those within the normal range (3.7 ± 0.4 vs 0.4 ± 0.1; p < 0.001). CONCLUSIONS & INFERENCES: The analysis of a large cohort of subjects using original techniques provides unique and heretofore unavailable information on the volume and distribution of intestinal gas in normal conditions and in relation to functional gastrointestinal symptoms. |
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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ BBB2015 | Serial | 2667 | ||
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Author | Fahad Shahbaz Khan; Jiaolong Xu; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez | ||||
Title | Recognizing Actions through Action-specific Person Detection | Type | Journal Article | ||
Year | 2015 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
Volume | 24 | Issue | 11 | Pages | 4422-4432 |
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Abstract | Action recognition in still images is a challenging problem in computer vision. To facilitate comparative evaluation independently of person detection, the standard evaluation protocol for action recognition uses an oracle person detector to obtain perfect bounding box information at both training and test time. The assumption is that, in practice, a general person detector will provide candidate bounding boxes for action recognition. In this paper, we argue that this paradigm is suboptimal and that action class labels should already be considered during the detection stage. Motivated by the observation that body pose is strongly conditioned on action class, we show that: 1) the existing state-of-the-art generic person detectors are not adequate for proposing candidate bounding boxes for action classification; 2) due to limited training examples, the direct training of action-specific person detectors is also inadequate; and 3) using only a small number of labeled action examples, the transfer learning is able to adapt an existing detector to propose higher quality bounding boxes for subsequent action classification. To the best of our knowledge, we are the first to investigate transfer learning for the task of action-specific person detection in still images. We perform extensive experiments on two benchmark data sets: 1) Stanford-40 and 2) PASCAL VOC 2012. For the action detection task (i.e., both person localization and classification of the action performed), our approach outperforms methods based on general person detection by 5.7% mean average precision (MAP) on Stanford-40 and 2.1% MAP on PASCAL VOC 2012. Our approach also significantly outperforms the state of the art with a MAP of 45.4% on Stanford-40 and 31.4% on PASCAL VOC 2012. We also evaluate our action detection approach for the task of action classification (i.e., recognizing actions without localizing them). For this task, our approach, without using any ground-truth person localization at test tim- , outperforms on both data sets state-of-the-art methods, which do use person locations. | ||||
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ISSN | 1057-7149 | ISBN | Medium | ||
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Notes | ADAS; LAMP; 600.076; 600.079 | Approved | no | ||
Call Number | Admin @ si @ KXR2015 | Serial | 2668 | ||
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Author | Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez | ||||
Title | Hierarchical Adaptive Structural SVM for Domain Adaptation | Type | Journal Article | ||
Year | 2016 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV |
Volume | 119 | Issue | 2 | Pages | 159-178 |
Keywords | Domain Adaptation; Pedestrian Detection | ||||
Abstract | A key topic in classification is the accuracy loss produced when the data distribution in the training (source) domain differs from that in the testing (target) domain. This is being recognized as a very relevant problem for many
computer vision tasks such as image classification, object detection, and object category recognition. In this paper, we present a novel domain adaptation method that leverages multiple target domains (or sub-domains) in a hierarchical adaptation tree. The core idea is to exploit the commonalities and differences of the jointly considered target domains. Given the relevance of structural SVM (SSVM) classifiers, we apply our idea to the adaptive SSVM (A-SSVM), which only requires the target domain samples together with the existing source-domain classifier for performing the desired adaptation. Altogether, we term our proposal as hierarchical A-SSVM (HA-SSVM). As proof of concept we use HA-SSVM for pedestrian detection, object category recognition and face recognition. In the former we apply HA-SSVM to the deformable partbased model (DPM) while in the rest HA-SSVM is applied to multi-category classifiers. We will show how HA-SSVM is effective in increasing the detection/recognition accuracy with respect to adaptation strategies that ignore the structure of the target data. Since, the sub-domains of the target data are not always known a priori, we shown how HA-SSVM can incorporate sub-domain discovery for object category recognition. |
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Publisher | Springer US | Place of Publication | Editor | ||
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ISSN | 0920-5691 | ISBN | Medium | ||
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Notes | ADAS; 600.085; 600.082; 600.076 | Approved | no | ||
Call Number | Admin @ si @ XRV2016 | Serial | 2669 | ||
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Author | G.Blasco; Simone Balocco; J.Puig; J.Sanchez-Gonzalez; W.Ricart; J.Daunis-I-Estadella; X.Molina; S.Pedraza; J.M.Fernandez-Real | ||||
Title | Carotid pulse wave velocity by magnetic resonance imaging is increased in middle-aged subjects with the metabolic syndrome | Type | Journal Article | ||
Year | 2015 | Publication | International Journal of Cardiovascular Imaging | Abbreviated Journal | ICJI |
Volume | 31 | Issue | 3 | Pages | 603-612 |
Keywords | Metabolic syndrome; Arterial stiffness; Pulse wave velocity; Carotid artery; Magnetic resonance | ||||
Abstract | Arterial pulse wave velocity (PWV), an independent predictor of cardiovascular disease, physiologically increases with age; however, growing evidence suggests metabolic syndrome (MetS) accelerates this increase. Magnetic resonance imaging (MRI) enables reliable noninvasive assessment of arterial stiffness by measuring arterial PWV in specific vascular segments. We investigated the association between the presence of MetS and its components with carotid PWV (cPWV) in asymptomatic subjects without diabetes. We assessed cPWV by MRI in 61 individuals (mean age, 55.3 ± 14.1 years; median age, 55 years): 30 with MetS and 31 controls with similar age, sex, body mass index, and LDL-cholesterol levels. The study population was dichotomized by the median age. To remove the physiological association between PWV and age, unpaired t tests and multiple regression analyses were performed using the residuals of the regression between PWV and age. cPWV was higher in middle-aged subjects with MetS than in those without (p = 0.001), but no differences were found in elder subjects (p = 0.313). cPWV was associated with diastolic blood pressure (r = 0.276, p = 0.033) and waist circumference (r = 0.268, p = 0.038). The presence of MetS was associated with increased cPWV regardless of age, sex, blood pressure, and waist (p = 0.007). The MetS components contributing independently to an increased cPWV were hypertension (p = 0.018) and hypertriglyceridemia (p = 0.002). The presence of MetS is associated with an increased cPWV in middle-aged subjects. In particular, hypertension and hypertriglyceridemia may contribute to early progression of carotid stiffness. | ||||
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Publisher | Springer Netherlands | Place of Publication | Editor | ||
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ISSN | 1569-5794 | ISBN | Medium | ||
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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ BBP2015 | Serial | 2670 | ||
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Author | Lluis Garrido; M.Guerrieri; Laura Igual | ||||
Title | Image Segmentation with Cage Active Contours | Type | Journal Article | ||
Year | 2015 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
Volume | 24 | Issue | 12 | Pages | 5557 - 5566 |
Keywords | Level sets; Mean value coordinates; Parametrized active contours; level sets; mean value coordinates | ||||
Abstract | In this paper, we present a framework for image segmentation based on parametrized active contours. The evolving contour is parametrized according to a reduced set of control points that form a closed polygon and have a clear visual interpretation. The parametrization, called mean value coordinates, stems from the techniques used in computer graphics to animate virtual models. Our framework allows to easily formulate region-based energies to segment an image. In particular, we present three different local region-based energy terms: 1) the mean model; 2) the Gaussian model; 3) and the histogram model. We show the behavior of our method on synthetic and real images and compare the performance with state-of-the-art level set methods. | ||||
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ISSN | 1057-7149 | ISBN | Medium | ||
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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ GGI2015 | Serial | 2673 | ||
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Author | David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados | ||||
Title | A Study of Bag-of-Visual-Words Representations for Handwritten Keyword Spotting | Type | Journal Article | ||
Year | 2015 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
Volume | 18 | Issue | 3 | Pages | 223-234 |
Keywords | Bag-of-Visual-Words; Keyword spotting; Handwritten documents; Performance evaluation | ||||
Abstract | The Bag-of-Visual-Words (BoVW) framework has gained popularity among the document image analysis community, specifically as a representation of handwritten words for recognition or spotting purposes. Although in the computer vision field the BoVW method has been greatly improved, most of the approaches in the document image analysis domain still rely on the basic implementation of the BoVW method disregarding such latest refinements. In this paper, we present a review of those improvements and its application to the keyword spotting task. We thoroughly evaluate their impact against a baseline system in the well-known George Washington dataset and compare the obtained results against nine state-of-the-art keyword spotting methods. In addition, we also compare both the baseline and improved systems with the methods presented at the Handwritten Keyword Spotting Competition 2014. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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Series Volume | Series Issue | Edition | |||
ISSN | 1433-2833 | ISBN | Medium | ||
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Notes | DAG; ADAS; 600.055; 600.061; 601.223; 600.077; 600.097 | Approved | no | ||
Call Number | Admin @ si @ ART2015 | Serial | 2679 | ||
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Author | David Roche | ||||
Title | A Statistical Framework for Terminating Evolutionary Algorithms at their Steady State | Type | Book Whole | ||
Year | 2015 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | As any iterative technique, it is a necessary condition a stop criterion for terminating Evolutionary Algorithms (EA). In the case of optimization methods, the algorithm should stop at the time it has reached a steady state so it can not improve results anymore. Assessing the reliability of termination conditions for EAs is of prime importance. A wrong or weak stop criterion can negatively aect both the computational eort and the nal result.
In this Thesis, we introduce a statistical framework for assessing whether a termination condition is able to stop EA at its steady state. In one hand a numeric approximation to steady states to detect the point in which EA population has lost its diversity has been presented for EA termination. This approximation has been applied to dierent EA paradigms based on diversity and a selection of functions covering the properties most relevant for EA convergence. Experiments show that our condition works regardless of the search space dimension and function landscape and Dierential Evolution (DE) arises as the best paradigm. On the other hand, we use a regression model in order to determine the requirements ensuring that a measure derived from EA evolving population is related to the distance to the optimum in xspace. Our theoretical framework is analyzed across several benchmark test functions and two standard termination criteria based on function improvement in f-space and EA population x-space distribution for the DE paradigm. Results validate our statistical framework as a powerful tool for determining the capability of a measure for terminating EA and select the x-space distribution as the best-suited for accurately stopping DE in real-world applications. |
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Address | July 2015 | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Debora Gil;Jesus Giraldo | |
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Notes | IAM; 600.075 | Approved | no | ||
Call Number | Admin @ si @ Roc2015 | Serial | 2686 | ||
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Author | Patricia Marquez | ||||
Title | A Confidence Framework for the Assessment of Optical Flow Performance | Type | Book Whole | ||
Year | 2015 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | Optical Flow (OF) is the input of a wide range of decision support systems such as car driver assistance, UAV guiding or medical diagnose. In these real situations, the absence of ground truth forces to assess OF quality using quantities computed from either sequences or the computed optical flow itself. These quantities are generally known as Confidence Measures, CM. Even if we have a proper confidence measure we still need a way to evaluate its ability to discard pixels with an OF prone to have a large error. Current approaches only provide a descriptive evaluation of the CM performance but such approaches are not capable to fairly compare different confidence measures and optical flow algorithms. Thus, it is of prime importance to define a framework and a general road map for the evaluation of optical flow performance.
This thesis provides a framework able to decide which pairs “ optical flow – confidence measure” (OF-CM) are best suited for optical flow error bounding given a confidence level determined by a decision support system. To design this framework we cover the following points: Descriptive scores. As a first step, we summarize and analyze the sources of inaccuracies in the output of optical flow algorithms. Second, we present several descriptive plots that visually assess CM capabilities for OF error bounding. In addition to the descriptive plots, given a plot representing OF-CM capabilities to bound the error, we provide a numeric score that categorizes the plot according to its decreasing profile, that is, a score assessing CM performance. Statistical framework. We provide a comparison framework that assesses the best suited OF-CM pair for error bounding that uses a two stage cascade process. First of all we assess the predictive value of the confidence measures by means of a descriptive plot. Then, for a sample of descriptive plots computed over training frames, we obtain a generic curve that will be used for sequences with no ground truth. As a second step, we evaluate the obtained general curve and its capabilities to really reflect the predictive value of a confidence measure using the variability across train frames by means of ANOVA. The presented framework has shown its potential in the application on clinical decision support systems. In particular, we have analyzed the impact of the different image artifacts such as noise and decay to the output of optical flow in a cardiac diagnose system and we have improved the navigation inside the bronchial tree on bronchoscopy. |
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Address | July 2015 | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Debora Gil;Aura Hernandez | |
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ISSN | ISBN | 978-84-943427-2-1 | Medium | ||
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Notes | IAM; 600.075 | Approved | no | ||
Call Number | Admin @ si @ Mar2015 | Serial | 2687 | ||
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Author | Marc Serra | ||||
Title | Modeling, estimation and evaluation of intrinsic images considering color information | Type | Book Whole | ||
Year | 2015 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | Image values are the result of a combination of visual information coming from multiple sources. Recovering information from the multiple factors thatproduced an image seems a hard and ill-posed problem. However, it is important to observe that humans develop the ability to interpret images and recognize and isolate specific physical properties of the scene.
Images describing a single physical characteristic of an scene are called intrinsic images. These images would benefit most computer vision tasks which are often affected by the multiple complex effects that are usually found in natural images (e.g. cast shadows, specularities, interreflections...). In this thesis we analyze the problem of intrinsic image estimation from different perspectives, including the theoretical formulation of the problem, the visual cues that can be used to estimate the intrinsic components and the evaluation mechanisms of the problem. |
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Address | September 2015 | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Robert Benavente;Olivier Penacchio | |
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ISSN | ISBN | 978-84-943427-4-5 | Medium | ||
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Notes | CIC; 600.074 | Approved | no | ||
Call Number | Admin @ si @ Ser2015 | Serial | 2688 | ||
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Author | L. Calvet; A. Ferrer; M. Gomes; A. Juan; David Masip | ||||
Title | Combining Statistical Learning with Metaheuristics for the Multi-Depot Vehicle Routing Problem with Market Segmentation | Type | Journal Article | ||
Year | 2016 | Publication | Computers & Industrial Engineering | Abbreviated Journal | CIE |
Volume | 94 | Issue | Pages | 93-104 | |
Keywords | Multi-Depot Vehicle Routing Problem; market segmentation applications; hybrid algorithms; statistical learning | ||||
Abstract | In real-life logistics and distribution activities it is usual to face situations in which the distribution of goods has to be made from multiple warehouses or depots to the nal customers. This problem is known as the Multi-Depot Vehicle Routing Problem (MDVRP), and it typically includes two sequential and correlated stages: (a) the assignment map of customers to depots, and (b) the corresponding design of the distribution routes. Most of the existing work in the literature has focused on minimizing distance-based distribution costs while satisfying a number of capacity constraints. However, no attention has been given so far to potential variations in demands due to the tness of the customerdepot mapping in the case of heterogeneous depots. In this paper, we consider this realistic version of the problem in which the depots are heterogeneous in terms of their commercial oer and customers show dierent willingness to consume depending on how well the assigned depot ts their preferences. Thus, we assume that dierent customer-depot assignment maps will lead to dierent customer-expenditure levels. As a consequence, market-segmentation strategiesneed to be considered in order to increase sales and total income while accounting for the distribution costs. To solve this extension of the MDVRP, we propose a hybrid approach that combines statistical learning techniques with a metaheuristic framework. First, a set of predictive models is generated from historical data. These statistical models allow estimating the demand of any customer depending on the assigned depot. Then, the estimated expenditure of each customer is included as part of an enriched objective function as a way to better guide the stochastic local search inside the metaheuristic framework. A set of computational experiments contribute to illustrate our approach and how the extended MDVRP considered here diers in terms of the proposed solutions from the traditional one. | ||||
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Publisher | PERGAMON-ELSEVIER SCIENCE LTD | Place of Publication | Editor | ||
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Series Editor | Series Title | Abbreviated Series Title | CIE | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0360-8352 | ISBN | Medium | ||
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Notes | OR;MV; | Approved | no | ||
Call Number | Admin @ si @ CFG2016 | Serial | 2749 | ||
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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 | ||||
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 | Mikhail Mozerov; Joost Van de Weijer | ||||
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 |
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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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ISSN | 1057-7149 | ISBN | Medium | ||
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Notes | LAMP; 600.079;ISE | Approved | no | ||
Call Number | Admin @ si @ MoW2015b | Serial | 2689 | ||
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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 | |
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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. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Bart Lamiroy; Jean-Marc Ogier | |
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Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-662-44853-3 | Medium | |
Area | Expedition | Conference ![]() |
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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 | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-662-44853-3 | Medium | |
Area | Expedition | Conference ![]() |
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Notes | DAG; 600.045; 600.055; 600.061; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RKL2014 | Serial | 2700 | ||
Permanent link to this record |