Now showing items 1-14 of 14

  • A Novel Algorithm for Ship Detection in SAR Imagery Based on the Wavelet Transform 

    Tello Alonso, Mª Victoria; López Martínez, Carlos; Mallorquí Franquet, Jordi Joan (IEEE, 2005-04-30)
    Article
    Open Access
    Carrying out an effective control of fishing activities is essential to guarantee a sustainable exploitation of sea resources. Nevertheless, as the regulated areas are extended, they are difficult and time consuming to ...
  • Content-based Video Summarization in Object Maps 

    Martos Asensio, Manuel (Universitat Politècnica de CatalunyaTechnische Universität Wien, 2013-09-10)
    Master thesis (pre-Bologna period)
    [ANGLÈS] The amount of digital video content available in the web is constantly increasing. Its handling requires efficient technologies: text search on large databases provides users a great amount of videos; the content ...
  • Contextless Object Recognition with Shape-enriched SIFT and Bags of Features 

    Tella Amo, Marcel (Universitat Politècnica de Catalunya, 2014-08-28)
    Master thesis (pre-Bologna period)
    Open Access
    Currently, there are highly competitive results in the field of object recognition based on the aggregation of point-based features [4, 26, 5, 6]. The aggregation process, typically with an average or max-pooling of the ...
  • DetectMe: object detection on the iPhone 

    Mingot Hidalgo, Josep Marc (Universitat Politècnica de Catalunya, 2013-12-19)
    Master thesis (pre-Bologna period)
    Open Access
    [ANGLÈS] DetectMe is one of the firsts apps to do the complete process of object detection on the iOS devices. With the app, the user is able to train a detector to detect any kind of objects and later on execute it on ...
  • Ego-Object Discovery in Lifelogging Datasets 

    Bolaños Solà, Marc (Universitat Politècnica de Catalunya, 2015-02)
    Master thesis
    Open Access
    En aquest treball proposem un mètode semi-supervisat per el descobriment d'objectes rellevants en seqüències d'imatges adquirides amb càmeres passives portàtils. Addicionalment, presentem un nou dataset d'imatges anotades ...
  • Fast online learning and detection of natural landmarks for autonomous aerial robots 

    Villamizar Vergel, Michael Alejandro; Sanfeliu Cortés, Alberto; Moreno-Noguer, Francesc (Institute of Electrical and Electronics Engineers (IEEE), 2014)
    Conference report
    Restricted access - publisher's policy
    We present a method for efficiently detecting natural landmarks that can handle scenes with highly repetitive patterns and targets progressively changing its appearance. At the core of our approach lies a Random Ferns ...
  • Learning RGB-D descriptors of garment parts for informed robot grasping 

    Ramisa Ayats, Arnau; Alenyà Ribas, Guillem; Moreno-Noguer, Francesc; Torras, Carme (2014)
    Article
    Open Access
    Robotic handling of textile objects in household environments is an emerging application that has recently received considerable attention thanks to the development of domestic robots. Most current approaches follow a ...
  • Object detection and recognition: from saliency prediction to one-shot trained detectors 

    Recasens Continente, Adrià (Universitat Politècnica de Catalunya, 2014-09-03)
    Master thesis (pre-Bologna period)
    12 months embargo
    [ANGLÈS] Computer vision capabilities have started to become available in smart devices this last years. The rapid growth of the smartphone world along with the big advance of the computer vision field in the last years ...
  • Object recognition applied to mobile robotics 

    Rigual Aparici, Ferran (Universitat Politècnica de Catalunya, 2012-09-19)
    Master thesis (pre-Bologna period)
    Open Access
    Investigació de les possibilitats dels mètodes actuals de detecció i reconeixement d'objectes. Adaptació del millor mètode seleccionat (MOPED) per tal de solucionar els problemes de la competició de robots domèstics "Robocup ...
  • Online human-assisted learning using random ferns 

    Villamizar Vergel, Michael Alejandro; Garrell Zulueta, Anais; Sanfeliu Cortés, Alberto; Moreno-Noguer, Francesc (2012)
    Conference report
    Open Access
    We present an Online Random Ferns (ORFs) classifier that progressively learns and builds enhanced models of object appearances. During the learning process, we allow the human intervention to assist the classifier and ...
  • Pedestrian Detection using a boosted cascade of Histogram of Oriented Gradients. 

    Ruiz Sancho, Cristina (Universitat Politècnica de Catalunya, 2014-09-10)
    Master thesis (pre-Bologna period)
    Open Access
    [ANGLÈS] Pedestrian detection has been an active area of research in recent years; its interest relies on the potential positive impact on quality of life of the related applications (surveillance systems, automotive safety, ...
  • Recognizing point clouds using conditional random fields 

    Husain, Syed Farzad; Dellen, Babette Karla Margarete; Torras, Carme (Institute of Electrical and Electronics Engineers (IEEE), 2014)
    Conference report
    Open Access
    Detecting objects in cluttered scenes is a necessary step for many robotic tasks and facilitates the interaction of the robot with its environment. Because of the availability of efficient 3D sensing devices as the Kinect, ...
  • Robust color contour object detection invariant to shadows 

    Scandaliaris, Jorge; Villamizar Vergel, Michael Alejandro; Andrade-Cetto, Juan; Sanfeliu Cortés, Alberto (Springer Verlag, 2007)
    Part of book or chapter of book
    Open Access
    In this work a new robust color and contour based object detection method in images with varying shadows is presented. The method relies on a physics-based contour detector that emphasizes material changes and a contour-based ...
  • Shared random Ferns for efficient detection of multiple categories 

    Villamizar Vergel, Michael Alejandro; Moreno-Noguer, Francesc; Andrade-Cetto, Juan; Sanfeliu Cortés, Alberto (2010)
    Conference report
    Open Access
    We propose a new algorithm for detecting multiple object categories that exploits the fact that different categories may share common features but with different geometric distributions. This yields an efficient detector ...