Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revisionPrevious revision
Next revision		Previous revision
teaching:gsoc2017 [2017/03/05 19:10] – [Topic 3: ROS with PR2 integration in Unreal Engine] ahaiduteaching:gsoc2017 [2017/03/17 18:21] (current) – [Topic 1: Multi-modal Cluttered Scene Analysis in Knowledge Intensive Scenarios] balintbe
Line 95: Line 95:
 would start from (but not necessarly limit ourselves to) the implemen- would start from (but not necessarly limit ourselves to) the implemen-
 tation of two state-of-the-art algorithms described in recent papers: tation of two state-of-the-art algorithms described in recent papers:
-[1] Ilya Lysenkov, Victor Eruhimov, and Gary Bradski, Recognition + 
-and Pose Estimation of Rigid Transparent Objects with a Kinect Sen- +[1] Aleksandrs Ecins, Cornelia Fermuller and Yiannis Aloimonos, Cluttered Scene Segmentation Using the Symmetry Constraint, International Conference on Robotics and Automation(ICRA) 2016
-sor, 2013 Robotics: Science and Systems Conference (RSS), 2013.+
 [2] Richtsfeld A., M ̈ [2] Richtsfeld A., M ̈
 orwald T., Prankl J., Zillich M. and Vincze orwald T., Prankl J., Zillich M. and Vincze
Line 106: Line 105:
 **Task Difficulty:** The task is considered to be challenging, as it is still a hot research topic where general solutions do not exist. **Task Difficulty:** The task is considered to be challenging, as it is still a hot research topic where general solutions do not exist.
      
-**Requirements:** Good programming skills in C++ and basic knowl- +**Requirements:** Good programming skills in C++ and basic knowledge of CMake and ROS. Experience with PCL, OpenCV is prefered.
-edge of CMake. Experience with PCL, OpenCV is prefered.+
  
 **Expected Results:** Currently the RoboSherlock framework lacks good perception algorithms that can generate object-hypotheses in challenging scenarios(clutter and/or occlusion). The expected results are several software components based on recent advances in cluttered scene analysis that are able to successfully recognized objects in the scenarios mentioned in the objectives, or a subset of these. **Expected Results:** Currently the RoboSherlock framework lacks good perception algorithms that can generate object-hypotheses in challenging scenarios(clutter and/or occlusion). The expected results are several software components based on recent advances in cluttered scene analysis that are able to successfully recognized objects in the scenarios mentioned in the objectives, or a subset of these.
- Impressum - Datenschutz



Prof. Dr. hc. Michael Beetz PhD
Head of Institute

Contact via
Andrea Cowley
assistant to Prof. Beetz
ai-office@cs.uni-bremen.de

Discover our VRB for innovative and interactive research


Memberships and associations:


Social Media: