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teaching:gsoc2017 [2017/03/17 18:21]
balintbe [Topic 1: Multi-modal Cluttered Scene Analysis in Knowledge Intensive Scenarios]
teaching:gsoc2017 [2017/03/17 18:21]
balintbe [Topic 1: Multi-modal Cluttered Scene Analysis in Knowledge Intensive Scenarios]
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 **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.
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-**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 and ROS. 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.