[ros-users] People stack state

[Miguel Prada Sarasola]

Hi Dejan,

I'll definitely have a look at those too. Thanks a lot!

Cheers,
Miguel.

El 14/09/2010, a las 02:20, Dejan Pangercic escribió:

> Hi Miguel,
> IAS at TUM also has some code for people detection on its own:
> a)laser based leg detection:
> http://tum-ros-pkg.svn.sourceforge.net/viewvc/tum-ros-pkg/perception/people_detector_node/
> (shall work out of the launch file with Hokuyo UTM 30 LX)
> b)http://tum-ros-pkg.svn.sourceforge.net/viewvc/tum-ros-pkg/perception/face_detector_mono/
> - is also based on openCV's Viola-Jones implementation but takes ROS
> images from a mono camera as an input.
> 
> cheers, D.
> 
> On Mon, Sep 13, 2010 at 5:18 PM, Miguel Prada Sarasola
> <miguel.prada.sarasola at gmail.com> wrote:
>> Thanks Mike. That's exactly what I was looking for.
>> Regards,
>> Miguel.
>> El 13/09/2010, a las 17:01, Michael Ferguson escribió:
>> 
>> You want to take a look at the people_experimental stack, which is where the
>> leg detector and people tracking code is.
>> 
>> -Mike
>> 
>> On Mon, Sep 13, 2010 at 5:49 AM, Miguel Prada Sarasola
>> <miguel.prada.sarasola at gmail.com> wrote:
>>> 
>>> Hi,
>>> 
>>> I'm trying to implement people detection and tracking for a mobile robot.
>>> I checked the 'people' stack, but the only algorithm that seems to be
>>> implemented is the cascade classifier for face detection in 'face_detector'
>>> package.
>>> 
>>> I remember having seen videos of the PR2 following people around the
>>> office at Willow, and I wonder if any of the code used there is available in
>>> any other stack or package, since it would be very useful to get something
>>> up and running quickly.
>>> 
>>> Also, is there any roadmap for further development in 'people' stack?
>>> Laser based leg detection? Hand detection?
>>> 
>>> Thanks in advance.
>>> 
>>> Regards,
>>> Miguel.
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>> 
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> 
> 
> 
> -- 
> MSc. Dejan Pangercic
> PhD Student/Researcher
> Intelligent Autonomous Systems Group
> Technische Universität München
> Telephone: +49 (89) 289-26908
> E-Mail: dejan.pangercic at cs.tum.edu
> WWW: http://ias.cs.tum.edu/people/pangercic
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