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Author Angel Sappa; Boris Vintimilla edit  openurl
  Title Cost-Based Closed Contour Representations Type Journal
  Year 2007 Publication Journal of Electronic Imaging, 16(2), 023009 (9 pages) Abbreviated Journal  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ SaV2007 Serial 803  
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Author Angel Sappa; M.A. Garcia edit  openurl
  Title Incremental Integration of Multiresolution Range Images Type Journal
  Year 2007 Publication The imaging science journal. Vol. 55, No. 3 pp. 127–139 Abbreviated Journal  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ SaG2007d Serial 812  
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Author Jaume Amores; N. Sebe; Petia Radeva edit  openurl
  Title Context-Based Object-Class Recognition and Retrieval by Generalized Correlograms Type Journal
  Year 2007 Publication IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29(10):1818–1833, (ISI 3,81) Abbreviated Journal  
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  Notes ADAS;MILAB Approved no  
  Call Number ADAS @ adas @ ASR2007b Serial 922  
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Author Yu Jie; Jaume Amores; N. Sebe; Petia Radeva; Tian Qi edit  openurl
  Title Distance Learning for Similarity Estimation Type Journal
  Year 2008 Publication IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.30(3):451–462 Abbreviated Journal  
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  Notes ADAS;MILAB Approved no  
  Call Number ADAS @ adas @ JAS2008 Serial 961  
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Author Joan Serrat; Ferran Diego; Felipe Lumbreras edit  openurl
  Title Los faros delanteros a traves del objetivo Type Journal
  Year 2008 Publication UAB Divulga, Revista de divulgacion cientifica Abbreviated Journal  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ SDL2008b Serial 1471  
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Author Carme Julia; Angel Sappa; Felipe Lumbreras edit  openurl
  Title Aprendiendo a recrear la realidad en 3D Type Journal
  Year 2008 Publication UAB Divulga, Revista de divulgacion cientifica Abbreviated Journal  
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  Notes spreading;ADAS Approved no  
  Call Number ADAS @ adas @ JSL2008b Serial 1472  
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Author Enrique Cabello; Cristina Conde; Angel Serrano; Licesio Rodriguez; David Vazquez edit   pdf
openurl 
  Title Empleo de sistemas biométricos para el reconocimiento de personas en aeropuertos Type Journal Article
  Year 2006 Publication Instituto Universitario de Investigación sobre Seguridad Interior (IUSI 2006) Abbreviated Journal  
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  Keywords Surveillance; Face detection; Face recognition  
  Abstract El presente proyecto se desarrolló a lo largo del año 2005, probando un prototipo de un sistema de verificación facial con imágenes extraídas de las cámaras de video vigilancia del aeropuerto de Barajas. Se diseñaron varios experimentos, agrupados en dos clases. En el primer tipo, el sistema es entrenado con imágenes obtenidas en condiciones de laboratorio y luego probado con imágenes extraídas de las cámaras de video vigilancia del aeropuerto de Barajas. En el segundo caso, tanto las imágenes de entrenamiento como las de prueba corresponden a imágenes extraídas de Barajas. Se ha desarrollado un sistema completo, que incluye adquisición y digitalización de las imágenes, localización y recorte de las caras en escena, verificación de sujetos y obtención de resultados. Los resultados muestran, que, en general, un sistema de verificación facial basado en imágenes puede ser una ayuda a un operario que deba estar vigilando amplias zonas.  
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  Notes invisible;ADAS Approved no  
  Call Number ADAS @ adas @ CCS2006a Serial 1672  
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Author Sergio Vera; Debora Gil; Antonio Lopez; Miguel Angel Gonzalez Ballester edit   pdf
url  openurl
  Title Multilocal Creaseness Measure Type Journal
  Year 2012 Publication The Insight Journal Abbreviated Journal IJ  
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  Keywords Ridges, Valley, Creaseness, Structure Tensor, Skeleton,  
  Abstract This document describes the implementation using the Insight Toolkit of an algorithm for detecting creases (ridges and valleys) in N-dimensional images, based on the Local Structure Tensor of the image. In addition to the filter used to calculate the creaseness image, a filter for the computation of the structure tensor is also included in this submission.  
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  Corporate Author Alma IT Systems Thesis  
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  Language english Summary Language english Original Title  
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  Notes IAM;ADAS; Approved no  
  Call Number IAM @ iam @ VGL2012 Serial 1840  
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Author David Vazquez; Jorge Bernal; F. Javier Sanchez; Gloria Fernandez-Esparrach; Antonio Lopez; Adriana Romero; Michal Drozdzal; Aaron Courville edit   pdf
url  openurl
  Title A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images Type Journal Article
  Year 2017 Publication Journal of Healthcare Engineering Abbreviated Journal JHCE  
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  Keywords Colonoscopy images; Deep Learning; Semantic Segmentation  
  Abstract Colorectal cancer (CRC) is the third cause of cancer death world-wide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for polyps and colonoscopy is the screening tool of choice. The main limitations of this screening procedure are polyp miss- rate and inability to perform visual assessment of polyp malignancy. These drawbacks can be reduced by designing Decision Support Systems (DSS) aim- ing to help clinicians in the different stages of the procedure by providing endoluminal scene segmentation. Thus, in this paper, we introduce an extended benchmark of colonoscopy image segmentation, with the hope of establishing a new strong benchmark for colonoscopy image analysis research. The proposed dataset consists of 4 relevant classes to inspect the endolumninal scene, tar- geting different clinical needs. Together with the dataset and taking advantage of advances in semantic segmentation literature, we provide new baselines by training standard fully convolutional networks (FCN). We perform a compar- ative study to show that FCN significantly outperform, without any further post-processing, prior results in endoluminal scene segmentation, especially with respect to polyp segmentation and localization.  
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  Notes ADAS; MV; 600.075; 600.085; 600.076; 601.281; 600.118 Approved no  
  Call Number VBS2017b Serial 2940  
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Author Zhijie Fang; Antonio Lopez edit  url
doi  openurl
  Title Intention Recognition of Pedestrians and Cyclists by 2D Pose Estimation Type Journal Article
  Year 2019 Publication IEEE Transactions on Intelligent Transportation Systems Abbreviated Journal TITS  
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  Abstract Anticipating the intentions of vulnerable road users (VRUs) such as pedestrians and cyclists is critical for performing safe and comfortable driving maneuvers. This is the case for human driving and, thus, should be taken into account by systems providing any level of driving assistance, from advanced driver assistant systems (ADAS) to fully autonomous vehicles (AVs). In this paper, we show how the latest advances on monocular vision-based human pose estimation, i.e. those relying on deep Convolutional Neural Networks (CNNs), enable to recognize the intentions of such VRUs. In the case of cyclists, we assume that they follow traffic rules to indicate future maneuvers with arm signals. In the case of pedestrians, no indications can be assumed. Instead, we hypothesize that the walking pattern of a pedestrian allows to determine if he/she has the intention of crossing the road in the path of the ego-vehicle, so that the ego-vehicle must maneuver accordingly (e.g. slowing down or stopping). In this paper, we show how the same methodology can be used for recognizing pedestrians and cyclists' intentions. For pedestrians, we perform experiments on the JAAD dataset. For cyclists, we did not found an analogous dataset, thus, we created our own one by acquiring and annotating videos which we share with the research community. Overall, the proposed pipeline provides new state-of-the-art results on the intention recognition of VRUs.  
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  Notes ADAS; no proj Approved no  
  Call Number Admin @ si @ FaL2019 Serial 3305  
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