Add in prior to get to MAP solution
With MAPSAC one could sample less than the
minimal number of points to make an estimate
(using prior as extra information)
Any posterior can be optimized; random sampling
good for matching and function optimization
– E.g. MAPSAC is a way to optimize objective functions
regardless of outliers or not