Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  consider the problem of computing large connected regions in a triangulated terrain of size n for which the normals of the triangles deviate by at most some small fixed angle. In previous work an exact near-quadratic algorithm was presented, but only a heuristic implementation with no guarantee was practicable.  present a new approximation algorithm for the problem which runs in O(n/∊2) time and—apart from giving a guarantee on the quality of the produced solution—has been implemented and shows good performance on real data sets representing fracture surfaces consisting of around half a million triangles. Further  present a simple approximation algorithm for a related problem: given a set of n points in the plane, determine the placement of the unit disk which contains most points. This algorithm runs in linear time as ll.
['Stefan Funke', 'Theocharis Malamatos', 'Rahul Ray']
I am writing a research paper on a idea FINDING PLANAR REGIONS IN A TERRAIN – IN PRACTICE AND WITH A GUARANTEE
[{"from": "human", "value": "I am writing a research paper on a idea FINDING PLANAR REGIONS IN A TERRAIN \u2013 IN PRACTICE AND WITH A GUARANTEE"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  consider the problem of computing large connected regions in a triangulated terrain of size n for which the normals of the triangles deviate by at most some small fixed angle. In previous work an exact near-quadratic algorithm was presented, but only a heuristic implementation with no guarantee was practicable.  present a new approximation algorithm for the problem which runs in O(n/\u220a2) time and\u2014apart from giving a guarantee on the quality of the produced solution\u2014has been implemented and shows good performance on real data sets representing fracture surfaces consisting of around half a million triangles. Further  present a simple approximation algorithm for a related problem: given a set of n points in the plane, determine the placement of the unit disk which contains most points. This algorithm runs in linear time as ll."}]