Computer Vision

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Notes from the Udacity Computer Vision Course taught by Georgia Tech professors.

Hough Transform

The Hough transform is a voting technique used to find things in images such as lines, circles, and arbitrary shapes.

Segmentation

Mean Shift Segmentation

  1. For every pixel (or a sample of pixels) in the image calculate some features such as (u,v)-color or (x,y, u, v) where xy are coordinates and uv are chroma.
  2. For each sampled pixel, or region of interest, calculate the new center-of-mass, or weighted-mean. The weights are typically Gaussian based on distance to the center. Repeat until convergence.
  3. The regions will cluster into modes. All regions which cluster to the same position are in the same attraction basin.

Attraction basin: the region for which all trajectories lead to the same mode.

Pros
  • Automatically finds basins of attraction.
  • Only one parameter: Window size for region of interest.
  • Does not assume any shape on cluster.
Cons
  • Need to pick a window size.
  • Doesn't scale well for high dimensions.