Marc,
I am giving it a try as we speak, thx a lot - I totally forgot about it.
cheers,d.
On Mon, Apr 11, 2011 at 9:28 PM, Marc Killpack <
staderennais@gmail.com> wrote:
> Hi Dejan,
> The pyramidal Lucas Kanade tracker in OpenCV
> (http://opencv.willowgarage.com/documentation/cpp/video_motion_analysis_and_object_tracking.html?highlight=lk#calcOpticalFlowPyrLK)
> tracks key features from frame to frame using optical flow. It can run at
> 15-30 Hz depending on the size of the image. It tracks each feature
> independently but is not extremely robust to large motions or changes in
> view angles between frames. If you have a good estimate of how some of the
> points are moving this can be fed into the algorithm. Also playing around
> with the pyramid terms (i.e. number of levels, size of feature window, etc)
> can help but your mileage may vary. I believe there is an lkdemo in the
> opencv2 ros package.
>
> In general this is good if you need frame rate feature tracking. Otherwise,
> from my limited experience, I think there are better methods for feature
> matching but this is worth a try.
>
> Marc Killpack
> Healthcare Robotics Lab - Georgia Tech
>
>
>
>
>> Date: Mon, 11 Apr 2011 18:14:02 +0200
>> From: Dejan Pangercic <dejan.pangercic@gmail.com>
>> Subject: [ros-users] Tracking of 2D Features in Images
>> To: User discussions <ros-users@code.ros.org>
>> Message-ID: <BANLkTi=YrNZBYsbNA+KPeCgSLDESmiuY7A@mail.gmail.com>
>> Content-Type: text/plain; charset=ISO-8859-1
>>
>> Dear ROS-istas,
>>
>> is anyone aware of an efficient package or library implementation that
>> performs the tracking of 2D features in images?
>> My aim is to find out which features are moving rigidly and which not
>> with respect to each other.
>>
>> Thx for your info and best, D.
>>
>> --
>> MSc. Dejan Pangercic
>> PhD Student/Researcher
>> Intelligent Autonomous Systems Group
>> Technische Universit?t M?nchen
>> Telephone: +49 (89) 289-26908
>> E-Mail: dejan.pangercic@cs.tum.edu
>> WWW: http://ias.cs.tum.edu/people/pangercic
>
>
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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@cs.tum.edu
WWW:
http://ias.cs.tum.edu/people/pangercic
(text/plain)