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Author Gioacchino Vino; Angel Sappa edit  doi
isbn  openurl
  Title Revisiting Harris Corner Detector Algorithm: a Gradual Thresholding Approach Type Conference Article
  Year 2013 Publication 10th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 7950 Issue Pages (down) 354-363  
  Keywords  
  Abstract This paper presents an adaptive thresholding approach intended to increase the number of detected corners, while reducing the amount of those ones corresponding to noisy data. The proposed approach works by using the classical Harris corner detector algorithm and overcome the difficulty in finding a general threshold that work well for all the images in a given data set by proposing a novel adaptive thresholding scheme. Initially, two thresholds are used to discern between strong corners and flat regions. Then, a region based criteria is used to discriminate between weak corners and noisy points in the midway interval. Experimental results show that the proposed approach has a better capability to reject false corners and, at the same time, to detect weak ones. Comparisons with the state of the art are provided showing the validity of the proposed approach.  
  Address Póvoa de Varzim; Portugal; June 2013  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-39093-7 Medium  
  Area Expedition Conference ICIAR  
  Notes ADAS; 600.055 Approved no  
  Call Number Admin @ si @ ViS2013 Serial 2562  
Permanent link to this record
 

 
Author Francisco Javier Orozco; Xavier Roca; Jordi Gonzalez edit  url
doi  openurl
  Title Real-Time Gaze Tracking with Appearance-Based Models Type Journal Article
  Year 2008 Publication Machine Vision Applications Abbreviated Journal MVAP  
  Volume 20 Issue 6 Pages (down) 353-364  
  Keywords Keywords Eyelid and iris tracking, Appearance models, Blinking, Iris saccade, Real-time gaze tracking  
  Abstract Psychological evidence has emphasized the importance of eye gaze analysis in human computer interaction and emotion interpretation. To this end, current image analysis algorithms take into consideration eye-lid and iris motion detection using colour information and edge detectors. However, eye movement is fast and and hence difficult to use to obtain a precise and robust tracking. Instead, our
method proposed to describe eyelid and iris movements as continuous variables using appearance-based tracking. This approach combines the strengths of adaptive appearance models, optimization methods and backtracking techniques.Thus,
in the proposed method textures are learned on-line from near frontal images and illumination changes, occlusions and fast movements are managed. The method achieves real-time performance by combining two appearance-based trackers to a
backtracking algorithm for eyelid estimation and another for iris estimation. These contributions represent a significant advance towards a reliable gaze motion description for HCI and expression analysis, where the strength of complementary
methodologies are combined to avoid using high quality images, colour information, texture training, camera settings and other time-consuming processes.
 
  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  
  Notes ISE Approved no  
  Call Number ISE @ ise @ ORG2008 Serial 972  
Permanent link to this record
 

 
Author Patricia Suarez; Angel Sappa; Boris X. Vintimilla edit   pdf
url  openurl
  Title Vegetation Index Estimation from Monospectral Images Type Conference Article
  Year 2018 Publication 15th International Conference on Images Analysis and Recognition Abbreviated Journal  
  Volume 10882 Issue Pages (down) 353-362  
  Keywords  
  Abstract This paper proposes a novel approach to estimate Normalized Difference Vegetation Index (NDVI) from just the red channel of a RGB image. The NDVI index is defined as the ratio of the difference of the red and infrared radiances over their sum. In other words, information from the red channel of a RGB image and the corresponding infrared spectral band are required for its computation. In the current work the NDVI index is estimated just from the red channel by training a Conditional Generative Adversarial Network (CGAN). The architecture proposed for the generative network consists of a single level structure, which combines at the final layer results from convolutional operations together with the given red channel with Gaussian noise to enhance
details, resulting in a sharp NDVI image. Then, the discriminative model
estimates the probability that the NDVI generated index came from the training dataset, rather than the index automatically generated. Experimental results with a large set of real images are provided showing that a Conditional GAN single level model represents an acceptable approach to estimate NDVI index.
 
  Address Povoa de Varzim; Portugal; June 2018  
  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 ICIAR  
  Notes MSIAU; 600.086; 600.130; 600.122 Approved no  
  Call Number Admin @ si @ SSV2018c Serial 3196  
Permanent link to this record
 

 
Author C. Santa-Marta; Jaume Garcia; A. Bajo; J.J. Vaquero; M. Ledesma-Carbayo; Debora Gil edit  openurl
  Title Influence of the Temporal Resolution on the Quantification of Displacement Fields in Cardiac Magnetic Resonance Tagged Images Type Conference Article
  Year 2008 Publication XXVI Congreso Anual de la Sociedad Española de Ingenieria Biomedica Abbreviated Journal  
  Volume Issue Pages (down) 352–353  
  Keywords  
  Abstract It is difficult to acquire tagged cardiac MR images with a high temporal and spatial resolution using clinical MR scanners. However, if such images are used for quantifying scores based on motion, it is essential a resolution as high as possibl e. This paper explores the influence of the temporal resolution of a tagged series on the quantification of myocardial dynamic parameters. To such purpose we have designed a SPAMM (Spatial Modulation of Magnetization) sequence allowing acquisition of sequences at simple and double temporal resolution. Sequences are processed to compute myocardial motion by an automatic technique based on the tracking of the harmonic phase of tagged images (the Harmonic Phase Flow, HPF). The results have been compared to manual tracking of myocardial tags. The error in displacement fields for double resolution sequences reduces 17%.  
  Address Valladolid  
  Corporate Author Thesis  
  Publisher Place of Publication Editor Roberto hornero, Saniel Abasolo  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CASEIB  
  Notes IAM; Approved no  
  Call Number IAM @ iam @ SGB2008 Serial 1033  
Permanent link to this record
 

 
Author Debora Gil; Petia Radeva; Jordi Saludes; J. Mauri edit   pdf
url  openurl
  Title Automatic Segmentation of Artery Wall in Coronary IVUS Images: A Probabilistic Approach Type Conference Article
  Year 2000 Publication International Conference on Pattern Recognition Abbreviated Journal  
  Volume 4 Issue Pages (down) 352-355  
  Keywords  
  Abstract Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, restenosis, etc). The poor quality of these images makes unsupervised segmentation based on traditional segmentation algorithms (such as edge or ridge/valley detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic templates to model and detect the shape of the vessel inner wall in IVUS images. We present the results of successful segmentation obtained from patients undergoing stent treatment. A physician team has validated these results.  
  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  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ GRS2000a Serial 1537  
Permanent link to this record
 

 
Author Carles Sanchez; Antonio Esteban Lansaque; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil edit   pdf
openurl 
  Title Towards a Videobronchoscopy Localization System from Airway Centre Tracking Type Conference Article
  Year 2017 Publication 12th International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume Issue Pages (down) 352-359  
  Keywords Video-bronchoscopy; Lung cancer diagnosis; Airway lumen detection; Region tracking; Guided bronchoscopy navigation  
  Abstract Bronchoscopists use fluoroscopy to guide flexible bronchoscopy to the lesion to be biopsied without any kind of incision. Being fluoroscopy an imaging technique based on X-rays, the risk of developmental problems and cancer is increased in those subjects exposed to its application, so minimizing radiation is crucial. Alternative guiding systems such as electromagnetic navigation require specific equipment, increase the cost of the clinical procedure and still require fluoroscopy. In this paper we propose an image based guiding system based on the extraction of airway centres from intra-operative videos. Such anatomical landmarks are matched to the airway centreline extracted from a pre-planned CT to indicate the best path to the nodule. We present a
feasibility study of our navigation system using simulated bronchoscopic videos and a multi-expert validation of landmarks extraction in 3 intra-operative ultrathin explorations.
 
  Address Porto; Portugal; February 2017  
  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 VISAPP  
  Notes IAM; 600.096; 600.075; 600.145 Approved no  
  Call Number Admin @ si @ SEB2017 Serial 2943  
Permanent link to this record
 

 
Author Mariella Dimiccoli; Cathal Gurrin; David J. Crandall; Xavier Giro; Petia Radeva edit  url
openurl 
  Title Introduction to the special issue: Egocentric Vision and Lifelogging Type Journal Article
  Year 2018 Publication Journal of Visual Communication and Image Representation Abbreviated Journal JVCIR  
  Volume 55 Issue Pages (down) 352-353  
  Keywords  
  Abstract  
  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  
  Notes MILAB; no proj Approved no  
  Call Number Admin @ si @ DGC2018 Serial 3187  
Permanent link to this record
 

 
Author Marçal Rusiñol; Josep Llados edit  openurl
  Title Flowchart Recognition in Patent Information Retrieval Type Book Chapter
  Year 2017 Publication Current Challenges in Patent Information Retrieval Abbreviated Journal  
  Volume 37 Issue Pages (down) 351-368  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor M. Lupu; K. Mayer; N. Kando; A.J. Trippe  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.097; 600.121 Approved no  
  Call Number Admin @ si @ RuL2017 Serial 2896  
Permanent link to this record
 

 
Author Spencer Low; Oliver Nina; Angel Sappa; Erik Blasch; Nathan Inkawhich edit   pdf
url  doi
openurl 
  Title Multi-Modal Aerial View Object Classification Challenge Results – PBVS 2022 Type Conference Article
  Year 2022 Publication IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) Abbreviated Journal  
  Volume Issue Pages (down) 350-358  
  Keywords  
  Abstract This paper details the results and main findings of the second iteration of the Multi-modal Aerial View Object Classification (MAVOC) challenge. The primary goal of both MAVOC challenges is to inspire research into methods for building recognition models that utilize both synthetic aperture radar (SAR) and electro-optical (EO) imagery. Teams are encouraged to develop multi-modal approaches that incorporate complementary information from both domains. While the 2021 challenge showed a proof of concept that both modalities could be used together, the 2022 challenge focuses on the detailed multi-modal methods. The 2022 challenge uses the same UNIfied Coincident Optical and Radar for recognitioN (UNICORN) dataset and competition format that was used in 2021. Specifically, the challenge focuses on two tasks, (1) SAR classification and (2) SAR + EO classification. The bulk of this document is dedicated to discussing the top performing methods and describing their performance on our blind test set. Notably, all of the top ten teams outperform a Resnet-18 baseline. For SAR classification, the top team showed a 129% improvement over baseline and an 8% average improvement from the 2021 winner. The top team for SAR + EO classification shows a 165% improvement with a 32% average improvement over 2021.  
  Address New Orleans; USA; June 2022  
  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 CVPRW  
  Notes MSIAU Approved no  
  Call Number Admin @ si @ LNS2022 Serial 3768  
Permanent link to this record
 

 
Author A. Pujol; Juan J. Villanueva edit  openurl
  Title A supervised Modification of the Hausdorff distance for visual shape classification Type Journal
  Year 2002 Publication International Journal of Pattern Recognition and Artificial Intelligence Abbreviated Journal  
  Volume 16 Issue 3 Pages (down) 349-359  
  Keywords  
  Abstract (IF: 0.359)  
  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  
  Notes ISE Approved no  
  Call Number PuV2002 Serial 273  
Permanent link to this record
 

 
Author Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke edit  openurl
  Title Writer Identification in Old Handwritten Music Scores Type Conference Article
  Year 2008 Publication Proceedings of the 8th International Workshop on Document Analysis Systems, Abbreviated Journal  
  Volume Issue Pages (down) 347–353  
  Keywords  
  Abstract  
  Address Nara (Japan)  
  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 DAS  
  Notes DAG Approved no  
  Call Number DAG @ dag @ FLS2008b Serial 1078  
Permanent link to this record
 

 
Author Patricia Suarez; Dario Carpio; Angel Sappa edit  url
doi  openurl
  Title Depth Map Estimation from a Single 2D Image Type Conference Article
  Year 2023 Publication 17th International Conference on Signal-Image Technology & Internet-Based Systems Abbreviated Journal  
  Volume Issue Pages (down) 347-353  
  Keywords  
  Abstract This paper presents an innovative architecture based on a Cycle Generative Adversarial Network (CycleGAN) for the synthesis of high-quality depth maps from monocular images. The proposed architecture leverages a diverse set of loss functions, including cycle consistency, contrastive, identity, and least square losses, to facilitate the generation of depth maps that exhibit realism and high fidelity. A notable feature of the approach is its ability to synthesize depth maps from grayscale images without the need for paired training data. Extensive comparisons with different state-of-the-art methods show the superiority of the proposed approach in both quantitative metrics and visual quality. This work addresses the challenge of depth map synthesis and offers significant advancements in the field.  
  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 SITIS  
  Notes MSIAU Approved no  
  Call Number Admin @ si @ SCS2023b Serial 4009  
Permanent link to this record
 

 
Author Anton Cervantes; Gemma Sanchez; Josep Llados; Agnes Borras; Ana Rodriguez edit   pdf
url  openurl
  Title Biometric Recognition Based on Line Shape Descriptors Type Book Chapter
  Year 2006 Publication Lecture Notes in Computer Science Abbreviated Journal  
  Volume 3926 Issue Pages (down) 346–357,  
  Keywords  
  Abstract Abstract. In this paper we propose biometric descriptors inspired by shape signatures traditionally used in graphics recognition approaches. In particular several methods based on line shape descriptors used to iden- tify newborns from the biometric information of the ears are developed. The process steps are the following: image acquisition, ear segmentation, ear normalization, feature extraction and identification. Several shape signatures are defined from contour images. These are formulated in terms of zoning and contour crossings descriptors. Experimental results are presented to demonstrate the effectiveness of the used techniques.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Link 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  
  Notes DAG Approved no  
  Call Number DAG @ dag @ CSL2006 Serial 685  
Permanent link to this record
 

 
Author Miquel Ferrer; Ernest Valveny; F. Serratosa edit  doi
isbn  openurl
  Title Median Graph Computation by means of a Genetic Approach Based on Minimum Common Supergraph and Maximum Common Subraph Type Conference Article
  Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 5524 Issue Pages (down) 346–353  
  Keywords  
  Abstract Given a set of graphs, the median graph has been theoretically presented as a useful concept to infer a representative of the set. However, the computation of the median graph is a highly complex task and its practical application has been very limited up to now. In this work we present a new genetic algorithm for the median graph computation. A set of experiments on real data, where none of the existing algorithms for the median graph computation could be applied up to now due to their computational complexity, show that we obtain good approximations of the median graph. Finally, we use the median graph in a real nearest neighbour classification showing that it leaves the box of the only-theoretical concepts and demonstrating, from a practical point of view, that can be a useful tool to represent a set of graphs.  
  Address Póvoa de Varzim, Portugal  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-02171-8 Medium  
  Area Expedition Conference IbPRIA  
  Notes DAG Approved no  
  Call Number DAG @ dag @ FVS2009c Serial 1174  
Permanent link to this record
 

 
Author Francesco Ciompi; Simone Balocco; Carles Caus; J. Mauri; Petia Radeva edit  doi
isbn  openurl
  Title Stent shape estimation through a comprehensive interpretation of intravascular ultrasound images Type Conference Article
  Year 2013 Publication 16th International Conference on Medical Image Computing and Computer Assisted Intervention Abbreviated Journal  
  Volume 8150 Issue 2 Pages (down) 345-352  
  Keywords  
  Abstract We present a method for automatic struts detection and stent shape estimation in cross-sectional intravascular ultrasound images. A stent shape is first estimated through a comprehensive interpretation of the vessel morphology, performed using a supervised context-aware multi-class classification scheme. Then, the successive strut identification exploits both local appearance and the defined stent shape. The method is tested on 589 images obtained from 80 patients, achieving a F-measure of 74.1% and an averaged distance between manual and automatic struts of 0.10 mm.  
  Address Nagoya; Japan; September 2013  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-40762-8 Medium  
  Area Expedition Conference MICCAI  
  Notes MILAB Approved no  
  Call Number Admin @ si @ CBC2013 Serial 2258  
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