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Author Katerine Diaz; Francesc J. Ferri edit  url
isbn  openurl
  Title Extensiones del método de vectores comunes discriminantes Aplicadas a la clasificación de imágenes Type Book Whole
  Year 2013 Publication (down) Extensiones del método de vectores comunes discriminantes Aplicadas a la clasificación de imágenes Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Los métodos basados en subespacios son una herramienta muy utilizada en aplicaciones de visión por computador. Aquí se presentan y validan algunos algoritmos que hemos propuesto en este campo de investigación. El primer algoritmo está relacionado con una extensión del método de vectores comunes discriminantes con kernel, que reinterpreta el espacio nulo de la matriz de dispersión intra-clase del conjunto de entrenamiento para obtener las características discriminantes. Dentro de los métodos basados en subespacios existen diferentes tipos de entrenamiento. Uno de los más populares, pero no por ello uno de los más eficientes, es el aprendizaje por lotes. En este tipo de aprendizaje, todas las muestras del conjunto de entrenamiento tienen que estar disponibles desde el inicio. De este modo, cuando nuevas muestras se ponen a disposición del algoritmo, el sistema tiene que ser reentrenado de nuevo desde cero. Una alternativa a este tipo de entrenamiento es el aprendizaje incremental. Aquí­ se proponen diferentes algoritmos incrementales del método de vectores comunes discriminantes.  
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  ISSN ISBN 978-3-639-55339-0 Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ DiF2013 Serial 2440  
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Author Niki Aifanti; Angel Sappa; N. Grammalidis; Sotiris Malassiotis edit  openurl
  Title Advances in Tracking and Recognition of Human Motion Type Book Chapter
  Year 2009 Publication (down) Encyclopedia of Information Science and Technology Abbreviated Journal  
  Volume I Issue 2nd edition Pages 65–71  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ ASG2009 Serial 1143  
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Author Antonio Lopez; Jiaolong Xu; Jose L. Gomez; David Vazquez; German Ros edit   pdf
openurl 
  Title From Virtual to Real World Visual Perception using Domain Adaptation -- The DPM as Example Type Book Chapter
  Year 2017 Publication (down) Domain Adaptation in Computer Vision Applications Abbreviated Journal  
  Volume Issue 13 Pages 243-258  
  Keywords Domain Adaptation  
  Abstract Supervised learning tends to produce more accurate classifiers than unsupervised learning in general. This implies that training data is preferred with annotations. When addressing visual perception challenges, such as localizing certain object classes within an image, the learning of the involved classifiers turns out to be a practical bottleneck. The reason is that, at least, we have to frame object examples with bounding boxes in thousands of images. A priori, the more complex the model is regarding its number of parameters, the more annotated examples are required. This annotation task is performed by human oracles, which ends up in inaccuracies and errors in the annotations (aka ground truth) since the task is inherently very cumbersome and sometimes ambiguous. As an alternative we have pioneered the use of virtual worlds for collecting such annotations automatically and with high precision. However, since the models learned with virtual data must operate in the real world, we still need to perform domain adaptation (DA). In this chapter we revisit the DA of a deformable part-based model (DPM) as an exemplifying case of virtual- to-real-world DA. As a use case, we address the challenge of vehicle detection for driver assistance, using different publicly available virtual-world data. While doing so, we investigate questions such as: how does the domain gap behave due to virtual-vs-real data with respect to dominant object appearance per domain, as well as the role of photo-realism in the virtual world.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor Gabriela Csurka  
  Language Summary Language Original Title  
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  Area Expedition Conference  
  Notes ADAS; 600.085; 601.223; 600.076; 600.118 Approved no  
  Call Number ADAS @ adas @ LXG2017 Serial 2872  
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Author German Ros; Laura Sellart; Gabriel Villalonga; Elias Maidanik; Francisco Molero; Marc Garcia; Adriana Cedeño; Francisco Perez; Didier Ramirez; Eduardo Escobar; Jose Luis Gomez; David Vazquez; Antonio Lopez edit  url
openurl 
  Title Semantic Segmentation of Urban Scenes via Domain Adaptation of SYNTHIA Type Book Chapter
  Year 2017 Publication (down) Domain Adaptation in Computer Vision Applications Abbreviated Journal  
  Volume 12 Issue Pages 227-241  
  Keywords SYNTHIA; Virtual worlds; Autonomous Driving  
  Abstract Vision-based semantic segmentation in urban scenarios is a key functionality for autonomous driving. Recent revolutionary results of deep convolutional neural networks (DCNNs) foreshadow the advent of reliable classifiers to perform such visual tasks. However, DCNNs require learning of many parameters from raw images; thus, having a sufficient amount of diverse images with class annotations is needed. These annotations are obtained via cumbersome, human labour which is particularly challenging for semantic segmentation since pixel-level annotations are required. In this chapter, we propose to use a combination of a virtual world to automatically generate realistic synthetic images with pixel-level annotations, and domain adaptation to transfer the models learnt to correctly operate in real scenarios. We address the question of how useful synthetic data can be for semantic segmentation – in particular, when using a DCNN paradigm. In order to answer this question we have generated a synthetic collection of diverse urban images, named SYNTHIA, with automatically generated class annotations and object identifiers. We use SYNTHIA in combination with publicly available real-world urban images with manually provided annotations. Then, we conduct experiments with DCNNs that show that combining SYNTHIA with simple domain adaptation techniques in the training stage significantly improves performance on semantic segmentation.  
  Address  
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  Publisher Springer Place of Publication Editor Gabriela Csurka  
  Language Summary Language Original Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS; 600.085; 600.082; 600.076; 600.118 Approved no  
  Call Number ADAS @ adas @ RSV2017 Serial 2882  
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Author David Geronimo; David Vazquez; Arturo de la Escalera edit  url
openurl 
  Title Vision-Based Advanced Driver Assistance Systems Type Book Chapter
  Year 2017 Publication (down) Computer Vision in Vehicle Technology: Land, Sea, and Air Abbreviated Journal  
  Volume Issue Pages  
  Keywords ADAS; Autonomous Driving  
  Abstract  
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  Notes ADAS; 600.118 Approved no  
  Call Number ADAS @ adas @ GVE2017 Serial 2881  
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Author Angel Sappa (ed) edit  isbn
openurl 
  Title Computer Graphics and Imaging Type Book Whole
  Year 2010 Publication (down) Computer Graphics and Imaging Abbreviated Journal  
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  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor Angel Sappa  
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  Series Volume Series Issue Edition  
  ISSN ISBN 978–0–88986–836–6 Medium  
  Area Expedition Conference CGIM  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ Sap2010 Serial 1468  
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Author Angel Sappa; George A. Triantafyllid edit  isbn
openurl 
  Title Computer Graphics and Imaging Type Book Whole
  Year 2012 Publication (down) Computer Graphics and Imaging Abbreviated Journal  
  Volume Issue Pages  
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  Address Crete, Greece  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN ISBN 978-0-88986-921-9 Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ Sap2012 Serial 2067  
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Author Angel Sappa; David Geronimo; Fadi Dornaika; Mohammad Rouhani; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title Moving object detection from mobile platforms using stereo data registration Type Book Chapter
  Year 2012 Publication (down) Computational Intelligence paradigms in advanced pattern classification Abbreviated Journal  
  Volume 386 Issue Pages 25-37  
  Keywords pedestrian detection  
  Abstract This chapter describes a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three main stages. Initially, feature points are extracted and tracked through consecutive 2D frames. Then, a RANSAC based approach is used for registering two point sets, with known correspondences in the 3D space. The computed 3D rigid displacement is used to map two consecutive 3D point clouds into the same coordinate system by means of the quaternion method. Finally, moving objects correspond to those areas with large 3D registration errors. Experimental results show the viability of the proposed approach to detect moving objects like vehicles or pedestrians in different urban scenarios.  
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  Publisher Springer Berlin Heidelberg Place of Publication Editor Marek R. Ogiela; Lakhmi C. Jain  
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  ISSN 1860-949X ISBN 978-3-642-24048-5 Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ SGD2012 Serial 2061  
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Author Jose Manuel Alvarez; Antonio Lopez edit  doi
isbn  openurl
  Title Photometric Invariance by Machine Learning Type Book Chapter
  Year 2012 Publication (down) Color in Computer Vision: Fundamentals and Applications Abbreviated Journal  
  Volume 7 Issue Pages 113-134  
  Keywords road detection  
  Abstract  
  Address  
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  Publisher iConcept Press Ltd Place of Publication Editor Theo Gevers, Arjan Gijsenij, Joost van de Weijer, Jan-Mark Geusebroek  
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  ISSN ISBN 978-0-470-89084-4 Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ AlL2012 Serial 2186  
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Author Fadi Dornaika; Angel Sappa edit  openurl
  Title SFM for Planar Scenes: a Direct and Robust Approach Type Book Chapter
  Year 2007 Publication (down) book chapter: Informatics in Control, Automation and Robotics II, Ed. J. Filipe, J. Ferrier, J. Cetto and M. Carvalho, pp. 129–136. (best papers ICINCO 2005) Abbreviated Journal  
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  Address Springer Verlag (Canada)  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ DoS2007b Serial 815  
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