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teaching:se-cv-ws14 [2014/10/27 14:33] balintbeteaching:se-cv-ws14 [2014/10/27 14:59] balintbe
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 Nähere Informationen zum Ablauf des Seminars finden sich [[https://elearning.uni-bremen.de/|hier]] Nähere Informationen zum Ablauf des Seminars finden sich [[https://elearning.uni-bremen.de/|hier]]
  
-Literature for Topics:+For a general overview about perception in robotics students are encouraged to look at the following paper : 
 +  * Vision for Robotics, //Markus Vincze and Danica Kragic// in Foundations and Trends in Robotics Vol. 1, No. 1 (2010) 1–78 [[http://www.nowpublishers.com/media/Journal-Article-PDFs/2300000001.pdf|[pdf]]]  
 + 
 +==Object Detecion and recogniotion==  
 +  *Richard Szeliski: Computer Vision:Algorithms and Applications, Chapter 14 [[http://szeliski.org/Book/|(link)]], 
 +  *Collet et.al. Object Recognition and Full Pose Registration from a Single Image for Robotic Manipulation 
 + 
 +==Hough Transform, RANSAC, ICP== 
 +  *Wikipedia is normally a great place for geting familiar with these algorithms 
 +  *Papzov et.el. An Efficient RANSAC for 3D Object Recognition in Noisy and Occluded Scenes 
 +  *Find more applications of these algorithms in robotics e.g.:  
 + 
 +==Tracking and Recognitizing Humans==  
 +  *Forsyth et.al. Computaional Studies of Human Motion: Part 1, Tracking and Motion Synthesis([[http://luthuli.cs.uiuc.edu/~daf/Papers-local/0600000005.pdf|pdf]]) 
 +  *Pons-Moll et.al. Metric Regression Forests for Human Pose Estimation( [[http://www.bmva.org/bmvc/2013/Papers/paper0004/paper0004.pdf|pdf]])
  
-|< 100% 33% 66%>| 
  
-^Object Detecion and recogniotion^ Richard Szeliski: Computer Vision:Algorithms and Applications, Chapter 14 [[http://szeliski.org/Book/|(link)]], \\ Collet et.al. Object Recognition and Full Pose Registration from a Single Image for Robotic Manipulation \\ ^ 
-^Hough, RANSAC, ICP^ Wikipedia is normally a great place for geting familiar with these algorithms\\ How are these applied in robotic perception? e.g.: Papzov et.el. An Efficient RANSAC for 3D Object Recognition in Noisy and Occluded Scenes^ 
  
  
  
  




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