Difference between revisions of "Face detection"
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|coordinator=AndreaBonarini | |coordinator=AndreaBonarini | ||
|tutor=AndreaBonarini;DavideRizzi | |tutor=AndreaBonarini;DavideRizzi | ||
| − | |students=GiulioFiscella; FedericoSem; | + | |students=GiulioFiscella; FedericoSem; |
|resarea=Robotics | |resarea=Robotics | ||
|restopic=Robot development | |restopic=Robot development | ||
|start=2010/04/15 | |start=2010/04/15 | ||
|end=2010/08/31 | |end=2010/08/31 | ||
| − | |status= | + | |status=Closed |
|level=Bs | |level=Bs | ||
|type=Thesis | |type=Thesis | ||
}} | }} | ||
| − | |||
Aim of this project was the development of a vision tracking system to be implemented for [[E-2? - A robot for exhibitions | E-2?]] in order to detect and follow, in a robust way, faces in uncostrained enviroment (i.e. an exhibition or mall environment). | Aim of this project was the development of a vision tracking system to be implemented for [[E-2? - A robot for exhibitions | E-2?]] in order to detect and follow, in a robust way, faces in uncostrained enviroment (i.e. an exhibition or mall environment). | ||
Revision as of 17:39, 28 April 2011
Face detection
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| Short Description: | Detect faces in a crowded environment |
| Coordinator: | AndreaBonarini (andrea.bonarini@polimi.it) |
| Tutor: | AndreaBonarini (andrea.bonarini@polimi.it), DavideRizzi () |
| Collaborator: | |
| Students: | GiulioFiscella (giulio.fiscella@torrescalla.it), FedericoSem (fede_sem@tele2.it) |
| Research Area: | Robotics |
| Research Topic: | Robot development |
| Start: | 2010/04/15 |
| End: | 2010/08/31 |
| Status: | Closed |
| Level: | Bs |
| Type: | Thesis |
Aim of this project was the development of a vision tracking system to be implemented for E-2? in order to detect and follow, in a robust way, faces in uncostrained enviroment (i.e. an exhibition or mall environment).
Our efforts have lead to an integration of different well known vision algorithms, implemented in C++ with the help of the opensource OpenCV libraries, which has proved to be much more reliable in the tracking tasks than the previous vision system, even if it is still affected by some detecting issues.
Here you can see a video showing the algorithm performance while working on a simple notebook webcam:
video to be uploaded...
Finally, this is a short video about a real time test on the robot.
video to be uploaded...
More details can be found in the discussion page.
