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Mini Projects Progress PDF Print E-mail
Written by University of Reading   
Friday, 04 April 2014 17:00

Camera Calibration

miniprojectsprogresscameracal

In the latest development, new features were introduced to improve the robustness of the camera self-calibration algorithm. In order to improve the calibration accuracy, the user had to provide vertical lines from structure and identify any areas which have occlusions.

In addition, three algorithms were introduced to minimise the influence of noise on the calibration. The first one was a shape analysis over the detected blob. Such analysis excluded the blobs that do not represent a person with both legs visible together.

The second algorithm is implemented to eliminate the image local noise. The last method replaced the Least Squares Fitting algorithm with the RANSAC fitting algorithm for better performance. All these modifications improved on the previous results significantly as shown in the Figure.

 
Progress Meeting at THALES PDF Print E-mail
Written by University of Reading   
Thursday, 20 February 2014 15:30

videosense 2014-02-12 001

A progress review meeting for VideoSense partners was held at the THALES premises, Vélizy Cedex, France on 12th February 2014.  The meeting agenda included the responses to the project Ethical Review followed by an immediate action plan.  The upcoming project deliverables were also discussed in order to tackle any possible problems.  Other general issues that have been tackled included Ethical trainings, Stakeholder meetings, Ethics board meetings, Mini projects progress, and finally the organisation of a Privacy Task at MediaEval 2014.  The meeting was successfully concluded by the end of the day.

 
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