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teaching:se-cv-ws14 [2014/10/27 14:33]
balintbe
teaching:se-cv-ws14 [2014/10/27 14:56]
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]]
  
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-^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^