Reading Ma 2004:Ch 11

Overview

1. Feature Detection
2. Feature Correspondence
3. Projective Reconstruction
4. Euclidean Reconstruction

Feature Detection

• Harris Detector
• Tiling
  • divide the image into, say, \(10\times10\) tiles
  • select features per tile
• Separation
  • one feature may cause several pixels to be marked as a corner
  • separation should be larger than the windows size used in detection
• Sorting by strength
  • sort first, and then select from top of the list
  • enforce separation from previously selected features

Feature Correspondence

• Small Baseline (motion video)
  • feature tracking - calculate motion
• Moderate Baseline (snapshots)
• Wide Baseline -> use SIFT or similar methods
  • the textbook is outdated on this point

Multiscale iterative feature tracking

TODO

Projective Reconstruction

Euclidean Reconstruction