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 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 >> Subject: [ros-users] Tracking of 2D Features in Images >> To: User discussions >> Message-ID: >> 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 > > > _______________________________________________ > ros-users mailing list > ros-users@code.ros.org > https://code.ros.org/mailman/listinfo/ros-users > > -- 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