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Author Hugo Berti; Angel Sappa; Osvaldo Agamennoni edit  openurl
  Title (up) Autonomous robot navigation with a global and asymptotic convergence Type Conference Article
  Year 2007 Publication IEEE International Conference on Robotics and Automation Abbreviated Journal  
  Volume Issue Pages 2712–2717  
  Keywords  
  Abstract  
  Address Roma (Italy)  
  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 ICRA  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ BSA2007 Serial 796  
Permanent link to this record
 
 
Author Josefina Mauri; Eduard Fernandez-Nofrerias; J. Comin; B. Garcia del Blanco; E. Iraculis; J.A. Gomez-Hospital; P. Valdovinos; F. Jara; A. Cequier; E. Esplugas; Oriol Pujol; Cristina Cañero; Debora Gil; Petia Radeva; Ricardo Toledo edit  openurl
  Title (up) Avaluació del Conjunt Stent/Artèria mitjançant ecografia intracoronària: lentorn informàtic Type Conference Article
  Year 2000 Publication Congrés de la Societat Catalana de Cardiologia. Abbreviated Journal  
  Volume Issue Pages  
  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 IAM;RV;MILAB;ADAS;HuPBA Approved no  
  Call Number IAM @ iam @ MNC2000 Serial 1622  
Permanent link to this record
 
 
Author Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados edit  url
doi  openurl
  Title (up) Browsing Heterogeneous Document Collections by a Segmentation-Free Word Spotting Method Type Conference Article
  Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 63-67  
  Keywords  
  Abstract In this paper, we present a segmentation-free word spotting method that is able to deal with heterogeneous document image collections. We propose a patch-based framework where patches are represented by a bag-of-visual-words model powered by SIFT descriptors. A later refinement of the feature vectors is performed by applying the latent semantic indexing technique. The proposed method performs well on both handwritten and typewritten historical document images. We have also tested our method on documents written in non-Latin scripts.  
  Address Beijing, China  
  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 ICDAR  
  Notes DAG;ADAS Approved no  
  Call Number Admin @ si @ RAT2011 Serial 1788  
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Author Konstantia Georgouli; Katerine Diaz; Jesus Martinez del Rincon; Anastasios Koidis edit  openurl
  Title (up) Building generic, easily-updatable chemometric models with harmonisation and augmentation features: The case of FTIR vegetable oils classification Type Conference Article
  Year 2017 Publication 3rd Ιnternational Conference Metrology Promoting Standardization and Harmonization in Food and Nutrition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Thessaloniki; Greece; October 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 IMEKOFOODS  
  Notes ADAS; 600.118 Approved no  
  Call Number Admin @ si @ GDM2017 Serial 3081  
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Author Diego Alejandro Cheda; Daniel Ponsa; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title (up) Camera Egomotion Estimation in the ADAS Context Type Conference Article
  Year 2010 Publication 13th International IEEE Annual Conference on Intelligent Transportation Systems Abbreviated Journal  
  Volume Issue Pages 1415–1420  
  Keywords  
  Abstract Camera-based Advanced Driver Assistance Systems (ADAS) have concentrated many research efforts in the last decades. Proposals based on monocular cameras require the knowledge of the camera pose with respect to the environment, in order to reach an efficient and robust performance. A common assumption in such systems is considering the road as planar, and the camera pose with respect to it as approximately known. However, in real situations, the camera pose varies along time due to the vehicle movement, the road slope, and irregularities on the road surface. Thus, the changes in the camera position and orientation (i.e., the egomotion) are critical information that must be estimated at every frame to avoid poor performances. This work focuses on egomotion estimation from a monocular camera under the ADAS context. We review and compare egomotion methods with simulated and real ADAS-like sequences. Basing on the results of our experiments, we show which of the considered nonlinear and linear algorithms have the best performance in this domain.  
  Address Madeira Island (Portugal)  
  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 2153-0009 ISBN 978-1-4244-7657-2 Medium  
  Area Expedition Conference ITSC  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ CPL2010 Serial 1425  
Permanent link to this record
 
 
Author Alexey Dosovitskiy; German Ros; Felipe Codevilla; Antonio Lopez; Vladlen Koltun edit   pdf
openurl 
  Title (up) CARLA: An Open Urban Driving Simulator Type Conference Article
  Year 2017 Publication 1st Annual Conference on Robot Learning. Proceedings of Machine Learning Abbreviated Journal  
  Volume 78 Issue Pages 1-16  
  Keywords Autonomous driving; sensorimotor control; simulation  
  Abstract We introduce CARLA, an open-source simulator for autonomous driving research. CARLA has been developed from the ground up to support development, training, and validation of autonomous urban driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely. The simulation platform supports flexible specification of sensor suites and environmental conditions. We use CARLA to study the performance of three approaches to autonomous driving: a classic modular pipeline, an endto-end
model trained via imitation learning, and an end-to-end model trained via
reinforcement learning. The approaches are evaluated in controlled scenarios of
increasing difficulty, and their performance is examined via metrics provided by CARLA, illustrating the platform’s utility for autonomous driving research.		  
  Address Mountain View; CA; USA; November 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 CORL  
  Notes ADAS; 600.085; 600.118 Approved no  
  Call Number Admin @ si @ DRC2017 Serial 2988  
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Author Daniel Ponsa; Antonio Lopez edit   pdf
openurl 
  Title (up) Cascade of Classifiers for Vehicle Detection Type Conference Article
  Year 2007 Publication Advanced Concepts for Intelligent Vision Systems, LNCS 4678, volume 1, pp. 980–989 Abbreviated Journal  
  Volume Issue Pages  
  Keywords vehicle detection  
  Abstract  
  Address Delft (Netherlands)  
  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 ADAS Approved no  
  Call Number ADAS @ adas @ PoL2007c Serial 935  
Permanent link to this record
 
 
Author Jaume Amores; N. Sebe; Petia Radeva edit  openurl
  Title (up) Class-Specific Binaryy Correlograms for Object Recognition Type Conference Article
  Year 2007 Publication British Machine Vision Conference Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Warwick (UK)  
  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 BMVC’07  
  Notes ADAS;MILAB Approved no  
  Call Number ADAS @ adas @ ASR2007a Serial 923  
Permanent link to this record
 
 
Author Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell; Antonio Lopez edit   pdf
url  doi
isbn  openurl
  Title (up) Color Attributes for Object Detection Type Conference Article
  Year 2012 Publication 25th IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 3306-3313  
  Keywords pedestrian detection  
  Abstract State-of-the-art object detectors typically use shape information as a low level feature representation to capture the local structure of an object. This paper shows that early fusion of shape and color, as is popular in image classification,
leads to a significant drop in performance for object detection. Moreover, such approaches also yields suboptimal results for object categories with varying importance of color and shape.
In this paper we propose the use of color attributes as an explicit color representation for object detection. Color attributes are compact, computationally efficient, and when combined with traditional shape features provide state-ofthe-
art results for object detection. Our method is tested on the PASCAL VOC 2007 and 2009 datasets and results clearly show that our method improves over state-of-the-art techniques despite its simplicity. We also introduce a new dataset consisting of cartoon character images in which color plays a pivotal role. On this dataset, our approach yields a significant gain of 14% in mean AP over conventional state-of-the-art methods.		  
  Address Providence; Rhode Island; USA;  
  Corporate Author Thesis  
  Publisher IEEE Xplore Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1063-6919 ISBN 978-1-4673-1226-4 Medium  
  Area Expedition Conference CVPR  
  Notes ADAS; CIC; Approved no  
  Call Number Admin @ si @ KRW2012 Serial 1935  
Permanent link to this record
 
 
Author Muhammad Anwer Rao; David Vazquez; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title (up) 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 ADAS @ adas @ RVL2011b Serial 1665  
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