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Author Victor Campmany; Sergio Silva; Juan Carlos Moure; Antoni Espinosa; David Vazquez; Antonio Lopez edit   pdf
openurl 
  Title GPU-based pedestrian detection for autonomous driving Type Abstract
  Year 2015 Publication Programming and Tunning Massive Parallel Systems Abbreviated Journal PUMPS  
  Volume Issue Pages  
  Keywords Autonomous Driving; ADAS; CUDA; Pedestrian Detection  
  Abstract Pedestrian detection for autonomous driving has gained a lot of prominence during the last few years. Besides the fact that it is one of the hardest tasks within computer vision, it involves huge computational costs. The real-time constraints in the field are tight, and regular processors are not able to handle the workload obtaining an acceptable ratio of frames per second (fps). Moreover, multiple cameras are required to obtain accurate results, so the need to speed up the process is even higher. Taking the work in [1] as our baseline, we propose a CUDA implementation of a pedestrian detection system. Further, we introduce significant algorithmic adjustments and optimizations to adapt the problem to the GPU architecture. The aim is to provide a system capable of running in real-time obtaining reliable results.  
  Address Barcelona; Spain  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title PUMPS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (up) PUMPS  
  Notes ADAS; 600.076; 600.082; 600.085 Approved no  
  Call Number ADAS @ adas @ CSM2015 Serial 2644  
Permanent link to this record
 

 
Author Sergio Silva; Victor Campmany; Laura Sellart; Juan Carlos Moure; Antoni Espinosa; David Vazquez; Antonio Lopez edit   pdf
openurl 
  Title Autonomous GPU-based Driving Type Abstract
  Year 2015 Publication Programming and Tunning Massive Parallel Systems Abbreviated Journal PUMPS  
  Volume Issue Pages  
  Keywords Autonomous Driving; ADAS; CUDA  
  Abstract Human factors cause most driving accidents; this is why nowadays is common to hear about autonomous driving as an alternative. Autonomous driving will not only increase safety, but also will develop a system of cooperative self-driving cars that will reduce pollution and congestion. Furthermore, it will provide more freedom to handicapped people, elderly or kids.

Autonomous Driving requires perceiving and understanding the vehicle environment (e.g., road, traffic signs, pedestrians, vehicles) using sensors (e.g., cameras, lidars, sonars, and radars), selflocalization (requiring GPS, inertial sensors and visual localization in precise maps), controlling the vehicle and planning the routes. These algorithms require high computation capability, and thanks to NVIDIA GPU acceleration this starts to become feasible.

NVIDIA® is developing a new platform for boosting the Autonomous Driving capabilities that is able of managing the vehicle via CAN-Bus: the Drive™ PX. It has 8 ARM cores with dual accelerated Tegra® X1 chips. It has 12 synchronized camera inputs for 360º vehicle perception, 4G and Wi-Fi capabilities allowing vehicle communications and GPS and inertial sensors inputs for self-localization.

Our research group has been selected for testing Drive™ PX. Accordingly, we are developing a Drive™ PX based autonomous car. Currently, we are porting our previous CPU based algorithms (e.g., Lane Departure Warning, Collision Warning, Automatic Cruise Control, Pedestrian Protection, or Semantic Segmentation) for running in the GPU.
 
  Address Barcelona; Spain  
  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 (up) PUMPS  
  Notes ADAS; 600.076; 600.082; 600.085 Approved no  
  Call Number ADAS @ adas @ SCS2015 Serial 2645  
Permanent link to this record
 

 
Author Daniel Hernandez; Alejandro Chacon; Antonio Espinosa; David Vazquez; Juan Carlos Moure; Antonio Lopez edit   pdf
openurl 
  Title Stereo Matching using SGM on the GPU Type Report
  Year 2016 Publication Programming and Tuning Massively Parallel Systems Abbreviated Journal PUMPS  
  Volume Issue Pages  
  Keywords CUDA; Stereo; Autonomous Vehicle  
  Abstract Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global Matching (SGM) is a widely used algorithm that propagates consistency constraints along several paths across the image. This work presents a real-time system producing reliable disparity estimation results on the new embedded energy efficient GPU devices. Our design runs on a Tegra X1 at 42 frames per second (fps) for an image size of 640x480, 128 disparity levels, and using 4 path directions for the SGM method.  
  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 (up) PUMPS  
  Notes ADAS; 600.085; 600.087; 600.076 Approved no  
  Call Number ADAS @ adas @ HCE2016b Serial 2776  
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Author Felipe Lumbreras; Xavier Roca; Daniel Ponsa; Robert Benavente; Judit Martinez; Silvia Sanchez; Coen Antens; Juan J. Villanueva edit  openurl
  Title Visual Inspection of Safety Belts Type Conference Article
  Year 2001 Publication International Conference on Quality Control by Artificial Vision Abbreviated Journal  
  Volume 2 Issue Pages 526–531  
  Keywords  
  Abstract  
  Address France  
  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 (up) QCAV  
  Notes ADAS;ISE;CIC Approved no  
  Call Number ADAS @ adas @ LRP2001 Serial 122  
Permanent link to this record
 

 
Author Fernando Barrera; Felipe Lumbreras; Cristhian Aguilera; Angel Sappa edit   pdf
openurl 
  Title Planar-Based Multispectral Stereo Type Conference Article
  Year 2012 Publication 11th Quantitative InfraRed Thermography Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Naples, 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 (up) QIRT  
  Notes ADAS Approved no  
  Call Number Admin @ si @ BLA2012 Serial 2016  
Permanent link to this record
 

 
Author Cristhian Aguilera; Fernando Barrera; Angel Sappa; Ricardo Toledo edit   pdf
openurl 
  Title A Novel SIFT-Like-Based Approach for FIR-VS Images Registration Type Conference Article
  Year 2012 Publication 11th Quantitative InfraRed Thermography Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Naples, 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 (up) QIRT  
  Notes ADAS; TV Approved no  
  Call Number Admin @ si @ ABS2012 Serial 2017  
Permanent link to this record
 

 
Author Josep Llados; Jaime Lopez-Krahe; Gemma Sanchez; Enric Marti edit  openurl
  Title Interprétation de cartes et plans par mise en correspondance de graphes de attributs Type Conference Article
  Year 2000 Publication 12 Congrès Francophone AFRIF–AFIA Abbreviated Journal  
  Volume 3 Issue Pages 225-234  
  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 (up) RFIA  
  Notes DAG;IAM Approved no  
  Call Number IAM @ iam @ LLS2000 Serial 1567  
Permanent link to this record
 

 
Author Clement Guerin; Christophe Rigaud; Karell Bertet; Jean-Christophe Burie; Arnaud Revel ; Jean-Marc Ogier edit  openurl
  Title Réduction de l’espace de recherche pour les personnages de bandes dessinées Type Conference Article
  Year 2014 Publication 19th National Congress Reconnaissance de Formes et l'Intelligence Artificielle Abbreviated Journal  
  Volume Issue Pages  
  Keywords contextual search; document analysis; comics characters  
  Abstract Les bandes dessinées représentent un patrimoine culturel important dans de nombreux pays et leur numérisation massive offre la possibilité d'effectuer des recherches dans le contenu des images. À ce jour, ce sont principalement les structures des pages et leurs contenus textuels qui ont été étudiés, peu de travaux portent sur le contenu graphique. Nous proposons de nous appuyer sur des éléments déjà étudiés tels que la position des cases et des bulles, pour réduire l'espace de recherche et localiser les personnages en fonction de la queue des bulles. L'évaluation de nos différentes contributions à partir de la base eBDtheque montre un taux de détection des queues de bulle de 81.2%, de localisation des personnages allant jusqu'à 85% et un gain d'espace de recherche de plus de 50%.  
  Address Rouen; Francia; July 2014  
  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 (up) RFIA  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ GRB2014 Serial 2480  
Permanent link to this record
 

 
Author Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias edit   pdf
doi  openurl
  Title Scene Representations for Autonomous Driving: an approach based on polygonal primitives Type Conference Article
  Year 2015 Publication 2nd Iberian Robotics Conference ROBOT2015 Abbreviated Journal  
  Volume 417 Issue Pages 503-515  
  Keywords Scene reconstruction; Point cloud; Autonomous vehicles  
  Abstract In this paper, we present a novel methodology to compute a 3D scene
representation. The algorithm uses macro scale polygonal primitives to model the scene. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Results show that the approach is capable of producing accurate descriptions of the scene. In addition, the algorithm is very efficient when compared to other techniques.
 
  Address Lisboa; Portugal; November 2015  
  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 (up) ROBOT  
  Notes ADAS; 600.076; 600.086 Approved no  
  Call Number Admin @ si @ OSS2015a Serial 2662  
Permanent link to this record
 

 
Author J.Poujol; Cristhian A. Aguilera-Carrasco; E.Danos; Boris X. Vintimilla; Ricardo Toledo; Angel Sappa edit   pdf
url  doi
isbn  openurl
  Title Visible-Thermal Fusion based Monocular Visual Odometry Type Conference Article
  Year 2015 Publication 2nd Iberian Robotics Conference ROBOT2015 Abbreviated Journal  
  Volume 417 Issue Pages 517-528  
  Keywords Monocular Visual Odometry; LWIR-RGB cross-spectral Imaging; Image Fusion.  
  Abstract The manuscript evaluates the performance of a monocular visual odometry approach when images from different spectra are considered, both independently and fused. The objective behind this evaluation is to analyze if classical approaches can be improved when the given images, which are from different spectra, are fused and represented in new domains. The images in these new domains should have some of the following properties: i) more robust to noisy data; ii) less sensitive to changes (e.g., lighting); iii) more rich in descriptive information, among other. In particular in the current work two different image fusion strategies are considered. Firstly, images from the visible and thermal spectrum are fused using a Discrete Wavelet Transform (DWT) approach. Secondly, a monochrome threshold strategy is considered. The obtained
representations are evaluated under a visual odometry framework, highlighting
their advantages and disadvantages, using different urban and semi-urban scenarios. Comparisons with both monocular-visible spectrum and monocular-infrared spectrum, are also provided showing the validity of the proposed approach.
 
  Address Lisboa; Portugal; November 2015  
  Corporate Author Thesis  
  Publisher Springer International Publishing Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2194-5357 ISBN 978-3-319-27145-3 Medium  
  Area Expedition Conference (up) ROBOT  
  Notes ADAS; 600.076; 600.086 Approved no  
  Call Number Admin @ si @ PAD2015 Serial 2663  
Permanent link to this record
 

 
Author Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras edit  url
openurl 
  Title The IIIA30 MObile Robot Object Recognition Datset Type Conference Article
  Year 2011 Publication 11th Portuguese Robotics Open Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Object perception is a key feature in order to make mobile robots able to perform high-level tasks. However, research aimed at addressing the constraints and limitations encountered in a mobile robotics scenario, like low image resolution, motion blur or tight computational constraints, is still very scarce. In order to facilitate future research in this direction, in this work we present an object detection and recognition dataset acquired using a mobile robotic platform. As a baseline for the dataset, we evaluated the cascade of weak classifiers object detection method from Viola and Jones.  
  Address Lisboa  
  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 (up) Robotica  
  Notes RV;ADAS Approved no  
  Call Number Admin @ si @ RAV2011 Serial 1777  
Permanent link to this record
 

 
Author Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades edit  openurl
  Title Spotting Symbol over Graphical Documents Via Sparsity in Visual Vocabulary Type Book Chapter
  Year 2016 Publication Recent Trends in Image Processing and Pattern Recognition Abbreviated Journal  
  Volume 709 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 (up) RTIP2R  
  Notes DAG Approved no  
  Call Number Admin @ si @ HTR2016 Serial 2956  
Permanent link to this record
 

 
Author Jaume Gibert; Ernest Valveny edit  doi
isbn  openurl
  Title Graph Embedding based on Nodes Attributes Representatives and a Graph of Words Representation. Type Conference Article
  Year 2010 Publication 13th International worshop on structural and syntactic pattern recognition and 8th international worshop on statistical pattern recognition Abbreviated Journal  
  Volume 6218 Issue Pages 223–232  
  Keywords  
  Abstract Although graph embedding has recently been used to extend statistical pattern recognition techniques to the graph domain, some existing embeddings are usually computationally expensive as they rely on classical graph-based operations. In this paper we present a new way to embed graphs into vector spaces by first encapsulating the information stored in the original graph under another graph representation by clustering the attributes of the graphs to be processed. This new representation makes the association of graphs to vectors an easy step by just arranging both node attributes and the adjacency matrix in the form of vectors. To test our method, we use two different databases of graphs whose nodes attributes are of different nature. A comparison with a reference method permits to show that this new embedding is better in terms of classification rates, while being much more faster.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor In E.R. Hancock, R.C. Wilson, T. Windeatt, I. Ulusoy and F. Escolano,  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-14979-5 Medium  
  Area Expedition Conference (up) S+SSPR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ GiV2010 Serial 1416  
Permanent link to this record
 

 
Author Youssef El Rhabi; Simon Loic; Brun Luc; Josep Llados; Felipe Lumbreras edit  doi
openurl 
  Title Information Theoretic Rotationwise Robust Binary Descriptor Learning Type Conference Article
  Year 2016 Publication Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR) Abbreviated Journal  
  Volume Issue Pages 368-378  
  Keywords  
  Abstract In this paper, we propose a new data-driven approach for binary descriptor selection. In order to draw a clear analysis of common designs, we present a general information-theoretic selection paradigm. It encompasses several standard binary descriptor construction schemes, including a recent state-of-the-art one named BOLD. We pursue the same endeavor to increase the stability of the produced descriptors with respect to rotations. To achieve this goal, we have designed a novel offline selection criterion which is better adapted to the online matching procedure. The effectiveness of our approach is demonstrated on two standard datasets, where our descriptor is compared to BOLD and to several classical descriptors. In particular, it emerges that our approach can reproduce equivalent if not better performance as BOLD while relying on twice shorter descriptors. Such an improvement can be influential for real-time applications.  
  Address Mérida; Mexico; November 2016  
  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 (up) S+SSPR  
  Notes DAG; ADAS; 600.097; 600.086 Approved no  
  Call Number Admin @ si @ RLL2016 Serial 2871  
Permanent link to this record
 

 
Author Sounak Dey; Anguelos Nicolaou; Josep Llados; Umapada Pal edit   pdf
doi  openurl
  Title Local Binary Pattern for Word Spotting in Handwritten Historical Document Type Conference Article
  Year 2016 Publication Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR) Abbreviated Journal  
  Volume Issue Pages 574-583  
  Keywords Local binary patterns; Spatial sampling; Learning-free; Word spotting; Handwritten; Historical document analysis; Large-scale data  
  Abstract Digital libraries store images which can be highly degraded and to index this kind of images we resort to word spotting as our information retrieval system. Information retrieval for handwritten document images is more challenging due to the difficulties in complex layout analysis, large variations of writing styles, and degradation or low quality of historical manuscripts. This paper presents a simple innovative learning-free method for word spotting from large scale historical documents combining Local Binary Pattern (LBP) and spatial sampling. This method offers three advantages: firstly, it operates in completely learning free paradigm which is very different from unsupervised learning methods, secondly, the computational time is significantly low because of the LBP features, which are very fast to compute, and thirdly, the method can be used in scenarios where annotations are not available. Finally, we compare the results of our proposed retrieval method with other methods in the literature and we obtain the best results in the learning free paradigm.  
  Address Merida; Mexico; December 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (up) S+SSPR  
  Notes DAG; 600.097; 602.006; 603.053 Approved no  
  Call Number Admin @ si @ DNL2016 Serial 2876  
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