Use in Shape Matching
A complete system that uses shape contexts for shape matching consists of the following steps (which will be covered in more detail in the Details of Implementation section):
- Randomly select a set of points that lie on the edges of a known shape and another set of points on an unknown shape.
- Compute the shape context of each point found in step 1.
- Match each point from the known shape to a point on an unknown shape. To minimize the cost of matching, first choose a transformation (e.g. affine, thin plate spline, etc.) that warps the edges of the known shape to the unknown (essentially aligning the two shapes). Then select the point on the unknown shape that most closely corresponds to each warped point on the known shape.
- Calculate the "shape distance" between each pair of points on the two shapes. Use a weighted sum of the shape context distance, the image appearance distance, and the bending energy (a measure of how much transformation is required to bring the two shapes into alignment).
- To identify the unknown shape, use a nearest-neighbor classifier to compare its shape distance to shape distances of known objects.
Read more about this topic: Shape Context
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