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Author Diego Cheda; Daniel Ponsa; Antonio Lopez edit   pdf
openurl 
  Title Monocular Egomotion Estimation based on Image Matching Type Conference Article
  Year 2012 Publication 1st International Conference on Pattern Recognition Applications and Methods Abbreviated Journal  
  Volume Issue Pages 425-430  
  Keywords SLAM  
  Abstract  
  Address 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 (up)  
  ISSN ISBN Medium  
  Area Expedition Conference ICPRAM  
  Notes ADAS Approved no  
  Call Number Admin @ si @ CPL2012a;; ADAS @ adas @ Serial 2011  
Permanent link to this record
 

 
Author Diego Cheda; Daniel Ponsa; Antonio Lopez edit   pdf
url  openurl
  Title Monocular Depth-based Background Estimation Type Conference Article
  Year 2012 Publication 7th International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume Issue Pages 323-328  
  Keywords  
  Abstract In this paper, we address the problem of reconstructing the background of a scene from a video sequence with occluding objects. The images are taken by hand-held cameras. Our method composes the background by selecting the appropriate pixels from previously aligned input images. To do that, we minimize a cost function that penalizes the deviations from the following assumptions: background represents objects whose distance to the camera is maximal, and background objects are stationary. Distance information is roughly obtained by a supervised learning approach that allows us to distinguish between close and distant image regions. Moving foreground objects are filtered out by using stationariness and motion boundary constancy measurements. The cost function is minimized by a graph cuts method. We demonstrate the applicability of our approach to recover an occlusion-free background in a set of sequences.  
  Address Roma  
  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 (up)  
  ISSN ISBN Medium  
  Area Expedition Conference VISAPP  
  Notes ADAS Approved no  
  Call Number Admin @ si @ CPL2012b; ADAS @ adas @ cpl2012e Serial 2012  
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Author Diego Cheda; Daniel Ponsa; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title Pedestrian Candidates Generation using Monocular Cues Type Conference Article
  Year 2012 Publication IEEE Intelligent Vehicles Symposium Abbreviated Journal  
  Volume Issue Pages 7-12  
  Keywords pedestrian detection  
  Abstract Common techniques for pedestrian candidates generation (e.g., sliding window approaches) are based on an exhaustive search over the image. This implies that the number of windows produced is huge, which translates into a significant time consumption in the classification stage. In this paper, we propose a method that significantly reduces the number of windows to be considered by a classifier. Our method is a monocular one that exploits geometric and depth information available on single images. Both representations of the world are fused together to generate pedestrian candidates based on an underlying model which is focused only on objects standing vertically on the ground plane and having certain height, according with their depths on the scene. We evaluate our algorithm on a challenging dataset and demonstrate its application for pedestrian detection, where a considerable reduction in the number of candidate windows is reached.  
  Address  
  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 (up)  
  ISSN 1931-0587 ISBN 978-1-4673-2119-8 Medium  
  Area Expedition Conference IV  
  Notes ADAS Approved no  
  Call Number Admin @ si @ CPL2012c; ADAS @ adas @ cpl2012d Serial 2013  
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