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Author Niki Aifanti; Angel Sappa; N. Grammalidis; Sotiris Malassiotis edit  openurl
  Title Human Motion Tracking and Recognition Type Book Chapter
  Year 2005 Publication Encyclopedia of Information Science and Technology, 1(5):1355–1360 Abbreviated Journal  
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  Notes Approved no  
  Call Number (up) ADAS @ adas @ ASG2005 Serial 496  
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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 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 (up) ADAS @ adas @ ASG2009 Serial 1143  
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Author Fadi Dornaika; Angel Sappa edit  openurl
  Title 3D Motion from Image Derivatives using the Least Trimmed Square Regression Type Book Chapter
  Year 2006 Publication International Workshop on Intelligent Computing in Pattern Analysis/Synthesis (IWICPAS´06), LNCS 4153: 76–84 Abbreviated Journal  
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  Address Xi'an (China)  
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  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ DoS2006b Serial 690  
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Author Fadi Dornaika; Angel Sappa edit  openurl
  Title Rigid and Non-Rigid Face Motion Tracking by Aligning Texture Maps and Stereo-Based 3D Models Type Book Chapter
  Year 2006 Publication 8th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS´06), LNCS 4179: 675–684 Abbreviated Journal  
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  Address Antwerp (Belgium)  
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  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ DoS2006c Serial 689  
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Author Fadi Dornaika; Angel Sappa edit  openurl
  Title 3D Face Tracking using Appearance Registration and Robust Iterative Closest Point Algorithm Type Book Chapter
  Year 2006 Publication 21st International Symposium on Computer and Information Sciences (ISCIS´06), LNCS 4263: 532–541 Abbreviated Journal  
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  Address Istanbul (Turkey)  
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  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ DoS2006d Serial 688  
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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 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  
  Volume Issue Pages  
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  Address Springer Verlag (Canada)  
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  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ DoS2007b Serial 815  
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Author Fadi Dornaika; Angel Sappa edit  openurl
  Title Real Time Image Registration for Planar Structure and 3D Sensor Pose Estimation Type Book Chapter
  Year 2008 Publication Stereo Vision Abbreviated Journal  
  Volume 18 Issue Pages 299–316  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor Asim Bhatti  
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  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ DoS2008c Serial 1057  
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Author David Geronimo; Angel Sappa; Antonio Lopez edit   pdf
url  openurl
  Title Stereo-based Candidate Generation for Pedestrian Protection Systems Type Book Chapter
  Year 2010 Publication Binocular Vision: Development, Depth Perception and Disorders Abbreviated Journal  
  Volume Issue 9 Pages 189–208  
  Keywords Pedestrian Detection  
  Abstract This chapter describes a stereo-based algorithm that provides candidate image windows to a latter 2D classification stage in an on-board pedestrian detection system. The proposed algorithm, which consists of three stages, is based on the use of both stereo imaging and scene prior knowledge (i.e., pedestrians are on the ground) to reduce the candidate searching space. First, a successful road surface fitting algorithm provides estimates on the relative ground-camera pose. This stage directs the search toward the road area thus avoiding irrelevant regions like the sky. Then, three different schemes are used to scan the estimated road surface with pedestrian-sized windows: (a) uniformly distributed through the road surface (3D); (b) uniformly distributed through the image (2D); (c) not uniformly distributed but according to a quadratic function (combined 2D-3D). Finally, the set of candidate windows is reduced by analyzing their 3D content. Experimental results of the proposed algorithm, together with statistics of searching space reduction are provided.  
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  Publisher NOVA Publishers Place of Publication Editor  
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  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ GSL2010 Serial 1301  
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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 Computer Vision in Vehicle Technology: Land, Sea, and Air Abbreviated Journal  
  Volume Issue Pages  
  Keywords ADAS; Autonomous Driving  
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  Notes ADAS; 600.118 Approved no  
  Call Number (up) ADAS @ adas @ GVE2017 Serial 2881  
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Author Felipe Lumbreras; Ramon Baldrich; Maria Vanrell; Joan Serrat; Juan J. Villanueva edit  openurl
  Title Multiresolution texture classification of ceramic tiles. Type Book Chapter
  Year 1999 Publication Recent Research developments in optical engineering, Research Signpost, 2: 213–228 Abbreviated Journal  
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  Address India  
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  Notes ADAS;CIC Approved no  
  Call Number (up) ADAS @ adas @ LBV1999b Serial 45  
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Author Antonio Lopez; Jiaolong Xu; Jose Luis 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 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  
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  Publisher Springer Place of Publication Editor Gabriela Csurka  
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  Notes ADAS; 600.085; 601.223; 600.076; 600.118 Approved no  
  Call Number (up) ADAS @ adas @ LXG2017 Serial 2872  
Permanent link to this record
 
 
Author Javier Marin; David Geronimo; David Vazquez; Antonio Lopez edit   pdf
isbn  openurl
  Title Pedestrian Detection: Exploring Virtual Worlds Type Book Chapter
  Year 2012 Publication Handbook of Pattern Recognition: Methods and Application Abbreviated Journal  
  Volume 5 Issue Pages 145-162  
  Keywords Virtual worlds; Pedestrian Detection; Domain Adaptation  
  Abstract Handbook of pattern recognition will include contributions from university educators and active research experts. This Handbook is intended to serve as a basic reference on methods and applications of pattern recognition. The primary aim of this handbook is providing the community of pattern recognition with a readable, easy to understand resource that covers introductory, intermediate and advanced topics with equal clarity. Therefore, the Handbook of pattern recognition can serve equally well as reference resource and as classroom textbook. Contributions cover all methods, techniques and applications of pattern recognition. A tentative list of relevant topics might include: 1- Statistical, structural, syntactic pattern recognition. 2- Neural networks, machine learning, data mining. 3- Discrete geometry, algebraic, graph-based techniques for pattern recognition. 4- Face recognition, Signal analysis, image coding and processing, shape and texture analysis. 5- Document processing, text and graphics recognition, digital libraries. 6- Speech recognition, music analysis, multimedia systems. 7- Natural language analysis, information retrieval. 8- Biometrics, biomedical pattern analysis and information systems. 9- Other scientific, engineering, social and economical applications of pattern recognition. 10- Special hardware architectures, software packages for pattern recognition.  
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  Publisher iConcept Press Place of Publication Editor  
  Language English Summary Language Original Title  
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  ISSN ISBN 978-1-477554-82-1 Medium  
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  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ MGV2012 Serial 1979  
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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 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  
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  Notes ADAS; 600.085; 600.082; 600.076; 600.118 Approved no  
  Call Number (up) ADAS @ adas @ RSV2017 Serial 2882  
Permanent link to this record
 
 
Author Angel Sappa; Fadi Dornaika edit  url
openurl 
  Title An Edge-Based Approach to Motion Detection Type Book Chapter
  Year 2006 Publication 6th International Conference on Computational Science (ICCS´06), LNCS 3991:563–570 Abbreviated Journal  
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  Address Reading (United Kingdom)  
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  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ SaD2006 Serial 654  
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Author Angel Sappa; Niki Aifanti; N. Grammalidis; Sotiris Malassiotis edit  isbn
openurl 
  Title Advances in Vision-Based Human Body Modeling Type Book Chapter
  Year 2004 Publication 3D Modeling & Animation: Systhesis and Analysis Techniques for the Human Body Abbreviated Journal  
  Volume Issue Pages 1-26  
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  Publisher Place of Publication Editor N. Sarris and M. Strintzis.  
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  ISSN ISBN 1-59140-299-9 Medium  
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  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ SAG2004a Serial 458  
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