Difference between revisions of "Accurate AR Marker Location"

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'''Expected outcome:'''
 
'''Expected outcome:'''
 
*C++ library to the robust localization of artificial markers
 
*C++ library to the robust localization of artificial markers
 +
*a ROS node performing accurate ARTag localization
 
*a comparison of Tags and algorithms in a real world scenario
 
*a comparison of Tags and algorithms in a real world scenario
 
*The use of this library in a SLAM framework (Thesis)
 
*The use of this library in a SLAM framework (Thesis)
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*C++ programming under Linux  
 
*C++ programming under Linux  
  
|tutor=MatteoMatteucci;SimoneCeriani
+
|tutor=MatteoMatteucci
|start=2012/04/01
+
|start=2015/01/01
 
|studmin=1
 
|studmin=1
 
|studmax=2
 
|studmax=2
|cfumin=10
+
|cfumin=5
|cfumax=20
+
|cfumax=10
 
|resarea=Computer Vision and Image Analysis
 
|resarea=Computer Vision and Image Analysis
 
|restopic=none
 
|restopic=none
 
|level=Bs;Ms
 
|level=Bs;Ms
|type=Thesis
+
|type=Thesis;Course
 
|status=Active
 
|status=Active
 
}}
 
}}

Latest revision as of 00:30, 22 December 2014

Title: C++ Library for accurate marker location based on subsequent pnp refinements
ARTag.jpg

Image:ARTag.jpg

Description: ARTags, QR codes, Data Matrix, are visual landmark used for augmented reality, but they could be used for robotics as well. A thesis has already been done on using data matrix for robot localization and mapping, but improvements are required in terms generality, accuracy and robustness of the solution. The goal is thuss to:
  • increase the number of markers supported by the system (ARTag + QR codes)
  • increase the accuracy of the detection and localization of the marker
  • test different algorithms for the solution of the perspective from n points problem

Material:

  • papers on PnP algorithms, OpenCV,
  • Matlab code with three PnP algorithms implementations
  • C++ libraries for marker detection (to be found and evaluated)

Expected outcome:

  • C++ library to the robust localization of artificial markers
  • a ROS node performing accurate ARTag localization
  • a comparison of Tags and algorithms in a real world scenario
  • The use of this library in a SLAM framework (Thesis)

Required skills or skills to be acquired:

  • background on computer vision and image processing
  • C++ programming under Linux
Tutor: MatteoMatteucci (matteo.matteucci@polimi.it)
Start: 2015/01/01
Students: 1 - 2
CFU: 5 - 10
Research Area: Computer Vision and Image Analysis
Research Topic: none
Level: Bs, Ms
Type: Thesis, Course
Status: Active