1. Real-Time Stereo Matching on Programmable Graphics Hardware Liang Wei

2. Motivation Use GPU to accelerate stereo matching Use GPU to accelerate stereo matching Free CPU power to do other important high level interpretation Free CPU power to do other important high level interpretation Direct output to graphics pipeline Direct output to graphics pipeline

3. Rendering Pipeline on Modern Graphics Hardware Geo. Primitive Vertex Processing Rasterization Fragment Processing Frame Buffer

4. Major steps in window-based Stereo Matching Alg. Cost Computation Cost Computation Cost Aggregation Cost Aggregation Disparity Selection Disparity Selection Disparity Refinement Disparity Refinement

5. Cost Computation Draw two screen-sized rectangles Draw two screen-sized rectangles Use fragment Prog. to compute per pixel difference Use fragment Prog. to compute per pixel difference

6. Cost Aggregation Use 4*4 window by enabling MIP- MAP or Linear Interpolation Use 4*4 window by enabling MIP- MAP or Linear Interpolation

7. Disparity Selection Can be efficiently done using Dept Test Can be efficiently done using Dept Test Encode Disparity as color, cost computed in previous steps as depth Encode Disparity as color, cost computed in previous steps as depth

8. Results

9. Results

10. Running time Use Tsukuba with size 382*288 Use Tsukuba with size 382*288 disparity range of 0-15 disparity range of 0-15 costs only 15ms on Pentium 4 3.20Ghz with NVidia GeForece 6800 costs only 15ms on Pentium 4 3.20Ghz with NVidia GeForece 6800 Graphics Card Graphics Card equivalent to 118MDe/s equivalent to 118MDe/s