Chan’s Algorithm
• It is Jarvis’s march applied to big blobs of
points
Chan’s algorithm
• Each blob is the convex hull of m points
• What is m ?
• m = min(exp(2, exp(2,t)), n)
Chan’s algorithm
• Partition P into r disjoint sets of size m
• Compute convex hull of each set
• Set p0 = (-∞, 0) and let p1 be the
bottommost point
• Do an m – step Jarvis march (note this)
• Stop if the march returns to p1 ,else
increase m and repeat
Chan’s algorithm
• Analysis
– Time-complexity in O(n log h)
» The time-complexity of each iteration is in O(n log m)
where m = exp(2, exp(2,t)), for t =1, 2, …
» Number of iterations is bounded above by log log h
» Thus the complexity is O(n exp(2, log log h + 1)).
This simplifies to O(n log h)