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Author Angel Sappa; Niki Aifanti; Sotiris Malassiotis; N. Grammalidis edit  openurl
  Title Survey of 3D Human Body Representations Type Book Chapter
  Year 2005 Publication Encyclopedia of Information Science and Technology, 1(5):2696–2701 Abbreviated Journal  
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  Notes Approved no  
  Call Number (down) ADAS @ adas @ SAM2005a Serial 497  
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Author Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis edit  openurl
  Title 3D Gait Estimation from Monoscopic Video Type Miscellaneous
  Year 2004 Publication IEEE International Conference on Image Processing Abbreviated Journal  
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  Address Singapore  
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  Notes ADAS Approved no  
  Call Number (down) ADAS @ adas @ SAM2004c Serial 495  
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Author Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis edit  openurl
  Title 3D Human Walking Modelling Type Book Whole
  Year 2004 Publication Articulated Motion and Deformable Objects, Third International Workshop, (AMDO 2004), Lecture Notes in Computer Science, F.J. Perales, B.A. Draper (Eds.), 3179:111–122 Abbreviated Journal  
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  Address Springer-Verlag, Berlin, Heidelberg  
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  Notes Approved no  
  Call Number (down) ADAS @ adas @ SAM2004b Serial 494  
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Author Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis edit  openurl
  Title Unsupervised Motion Classification by means of Efficient Feature Selection and Tracking Type Miscellaneous
  Year 2004 Publication IEEE Int. Symp. on 3D Data Processing, Visualization and Transmission Abbreviated Journal  
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  Address Thessaloniki (Greece)  
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  Notes Approved no  
  Call Number (down) ADAS @ adas @ SAM2004a Serial 456  
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Author Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis edit  openurl
  Title Monocular 3D Human Body Reconstruction Towards Depth Augmentation of Television Sequences Type Conference Article
  Year 2003 Publication IEEE International Conference on Image Processing, Barcelona, Spain, September 2003 Abbreviated Journal  
  Volume Issue Pages 325-328  
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  Address Barcelona  
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  Notes ADAS Approved no  
  Call Number (down) ADAS @ adas @ SAM2003 Serial 418  
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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 (down) ADAS @ adas @ SaG2007d Serial 812  
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Author Angel Sappa; M.A. Garcia edit  openurl
  Title Aprendiendo a recrear la realidad en 3D Type Journal
  Year 2007 Publication UAB Divulga, Revista de Divulgacion Cientifica Abbreviated Journal  
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  Notes spreading Approved no  
  Call Number (down) ADAS @ adas @ SaG2007c Serial 1470  
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Author Angel Sappa; M.A. Garcia edit  openurl
  Title Coarse-to-Fine Approximation of Range Images with Bounded Error Adaptive Triangular Meshes Type Journal
  Year 2007 Publication Journal of Electronic Imaging, 16(2), 023010(11 pages) Abbreviated Journal  
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  Notes ADAS Approved no  
  Call Number (down) ADAS @ adas @ SaG2007b Serial 802  
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Author Angel Sappa; M.A. Garcia edit  openurl
  Title Generating compact representations of static scenes by means of 3D object hierarchies Type Journal
  Year 2007 Publication The Visual Computer, 23(2): 143–154 Abbreviated Journal  
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  Notes ADAS Approved no  
  Call Number (down) ADAS @ adas @ SaG2007a Serial 798  
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Author Angel Sappa; M.A. Garcia edit  openurl
  Title Hierarchical Clustering of 3D Objects and its Application to Minimum Distance Computation Type Conference Article
  Year 2004 Publication IEEE International Conference on Robotics & Automation, 5287–5292, New Orleans, LA (USA), ISBN: 0–7803–8232–3 Abbreviated Journal  
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  Address New Orleans, LA, USA  
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  Notes ADAS Approved no  
  Call Number (down) ADAS @ adas @ SaG2004b Serial 459  
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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 (down) ADAS @ adas @ SAG2004a Serial 458  
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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 (down) ADAS @ adas @ SaD2006 Serial 654  
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Author Muhammad Anwer Rao; David Vazquez; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title Color Contribution to Part-Based Person Detection in Different Types of Scenarios Type Conference Article
  Year 2011 Publication 14th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal  
  Volume 6855 Issue II Pages 463-470  
  Keywords Pedestrian Detection; Color  
  Abstract Camera-based person detection is of paramount interest due to its potential applications. The task is diffcult because the great variety of backgrounds (scenarios, illumination) in which persons are present, as well as their intra-class variability (pose, clothe, occlusion). In fact, the class person is one of the included in the popular PASCAL visual object classes (VOC) challenge. A breakthrough for this challenge, regarding person detection, is due to Felzenszwalb et al. These authors proposed a part-based detector that relies on histograms of oriented gradients (HOG) and latent support vector machines (LatSVM) to learn a model of the whole human body and its constitutive parts, as well as their relative position. Since the approach of Felzenszwalb et al. appeared new variants have been proposed, usually giving rise to more complex models. In this paper, we focus on an issue that has not attracted suficient interest up to now. In particular, we refer to the fact that HOG is usually computed from RGB color space, but other possibilities exist and deserve the corresponding investigation. In this paper we challenge RGB space with the opponent color space (OPP), which is inspired in the human vision system.We will compute the HOG on top of OPP, then we train and test the part-based human classifer by Felzenszwalb et al. using PASCAL VOC challenge protocols and person database. Our experiments demonstrate that OPP outperforms RGB. We also investigate possible differences among types of scenarios: indoor, urban and countryside. Interestingly, our experiments suggest that the beneficts of OPP with respect to RGB mainly come for indoor and countryside scenarios, those in which the human visual system was designed by evolution.  
  Address Seville, Spain  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Berlin Heidelberg Editor P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch  
  Language English Summary Language english Original Title Color Contribution to Part-Based Person Detection in Different Types of Scenarios  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-23677-8 Medium  
  Area Expedition Conference CAIP  
  Notes ADAS Approved no  
  Call Number (down) ADAS @ adas @ RVL2011b Serial 1665  
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Author Muhammad Anwer Rao; David Vazquez; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title Opponent Colors for Human Detection Type Conference Article
  Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 6669 Issue Pages 363-370  
  Keywords Pedestrian Detection; Color; Part Based Models  
  Abstract Human detection is a key component in fields such as advanced driving assistance and video surveillance. However, even detecting non-occluded standing humans remains a challenge of intensive research. Finding good features to build human models for further detection is probably one of the most important issues to face. Currently, shape, texture and motion features have deserve extensive attention in the literature. However, color-based features, which are important in other domains (e.g., image categorization), have received much less attention. In fact, the use of RGB color space has become a kind of choice by default. The focus has been put in developing first and second order features on top of RGB space (e.g., HOG and co-occurrence matrices, resp.). In this paper we evaluate the opponent colors (OPP) space as a biologically inspired alternative for human detection. In particular, by feeding OPP space in the baseline framework of Dalal et al. for human detection (based on RGB, HOG and linear SVM), we will obtain better detection performance than by using RGB space. This is a relevant result since, up to the best of our knowledge, OPP space has not been previously used for human detection. This suggests that in the future it could be worth to compute co-occurrence matrices, self-similarity features, etc., also on top of OPP space, i.e., as we have done with HOG in this paper.  
  Address Las Palmas de Gran Canaria. Spain  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Berlin Heidelberg Editor J. Vitria; J.M. Sanches; M. Hernandez  
  Language English Summary Language English Original Title Opponent Colors for Human Detection  
  Series Editor Series Title Lecture Notes on Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-21256-7 Medium  
  Area Expedition Conference IbPRIA  
  Notes ADAS Approved no  
  Call Number (down) ADAS @ adas @ RVL2011a Serial 1666  
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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 (down) ADAS @ adas @ RSV2017 Serial 2882  
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