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Basic approach:
-  Nodes of the tree represent a scene to model primitive (e.g. edge,
surface) match.
 -  Let Tree have m branches at each node that correspond to model
primitives.
 -  Let level of tree represent a model primitive.
 -  The level and node position specify a match pair.
 -  Use a  tree searching strategy (see below for methods used) to find a match.
 -  One traversal through tree gives a match list -- a possible match
of scene to model features.
 -  Representation called a search or interpretation tree.
 
  
Fig. 
 Interpretation tree
How do we perform matching?
-  At each level of the tree, one  of the edges from the scene is matched
with each of the m possible edges in the model.
 -  Each node has m children
representing taking the match proposed so far together with all possible matches
for the current scene
edge.
 -  A transformation representing the match so far can be maintained.
 -  Search tree in depth first manner and pruned by
rejecting interpretations that fail to satisfy current match.
 -  The search space is large -- 
 possible combinations for n scene
primitives.
 -  A lot of computations?
 
We can reduce the computational overheads by employing some local geometric
constraints to prune the tree further.
These are:
-  Cheap to compute and employ.
 -  applied before the transformation test.
 
For Edges we could employ:
- Distance Constraint
 -  -- The length of the sensed edge must be less than
or equal to the length of the model edge under consideration.
	
 - Angle Constraint
 -  -- The angle between two adjacent sensed edges must
agree with that between the two corresponding matched model edges.
	
 - Direction Constraint
 -  -- Let 
 represent the range of
vectors from any point on sensed edge a to any point on sensed edge b. In an
interpretation which respectively pairs sensed edges a and b with model edges
i and j, this range of vectors must be compatible with the range of vectors
produced by i and j.
 
For Surface we could employ:
-  Angles between planes.
 -  Area of planes.
 -  Invariants.
 -  Measures of curvature.
 
 
 
   
 Next: Some Matching Case Studies
Up: Model Based Object Recognition
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dave@cs.cf.ac.uk