Enhanced Motion Blur Calculation with Optical Flow

Supervision:





Background:

Optical Flow is a method to compute an approximate motion field in an image sequence. Normally the motion can only be detected at image boundaries such as edges but in most applications one wants to have a dense motion field, i.e. a motion vector at every point in the image. Therefore a variational formulation of the optical flow problem is used including the assumptions of a smooth motion field and a constant gray value of a single point. The latter means that changes in the illumination of the scene are ignored. This simple model makes it possible to compute the optical flow very efficiently.

Computing motion blur is a complex task even for modern raytracers. An alternative approach to temporal sampling is to used image based techniques. These have e.g. been applied to stop motion animations. The topic of this thesis will be to use information gained from the optical flow algorithm, as described above, to enhance image based motion blur computations.



Tasks:

Further Information:


Status:

Finished