1. Deliverable 2.2: Demonstrator on Multiscale Motion Estimation Florian Becker, Jing Yuan, Christoph Schnörr CVGPR group, University of Mannheim

2. Multiscale Filter Library Implementation:ANSI C Interface: C/C++ and Matlab (MEX) Lowpass-filter: binomial filters Resampling: spline interpolation (degree 2 to 5) Scaling factor: selectable

3. Multiscale Motion Estimation Demonstrator 2.2 Implementation: Matlab Multiscale framework for motion estimation: dyadic image pyramid → multiscale filter library underlying singlescale motion estimator → Lucas/Kanade image warping → spline interpolation warp rescaling → spline interpolation evaluation: synthetic PIV data

4. Spline Interpolation: 360° Rotation in 23 Steps original cubic spline bicubic bilinear

5. Spline Interpolation: 10 x Zoom bilinear cubic spline

6. ↓↓ ↑ ↓↓ ↑ W W E+ scale down scale up warp image estimate warp join warps ← next coarser levelnext finer level →

7. Regularisation of Local Flow Estimation Replace data term in variational approaches M and d: from multiscale Lucas/Kanade estimator Definition: compact ASCII file format for data term Example: Horn/Schunck with replaced data term

8. PIV image New Data Term confidential measurement local estimation

9. Horn/Schunck with New Data Term λ=0 λ=10 -4 λ=10 -2