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Stereo Rectification

Stereo Rectification. Detect feature points for rectification using SIFT. Interpolation. Truncated separable approximation to an isotropic Laplacian kernel. Advantages: Large support windows Separable: efficient GPU implementation fewer costly texture fetches needed

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Stereo Rectification

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  1. Stereo Rectification • Detect feature points for rectification using SIFT

  2. Interpolation • Truncated separable approximation to an isotropic Laplacian kernel. • Advantages: • Large support windows • Separable: efficient GPU implementation • fewer costly texture fetches needed • Boundary-guided, less foreground-fattening • Cost = min(UL, UR, BL, BR, L, U, R, B, F)

  3. Very Small Baseline • Baseline = 0.5 – 1 cm Left Right Middle

  4. Limited Depth Resolution

  5. SmallBaseline • Baseline = 2 – 5 cm Left input Right input Middle

  6. Wider Baseline • Baseline = 7 – 10 cm Left input Right input Middle - basic Middle – truncated

  7. Cg vs CUDA

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