Mostly of us are familiar with the convex hull problem,
I'm trying to solve a similar/related problem: the inner (circunscribed) convex hull, which basicaaly means finding the largest polygon to be fit inside a set of points.
In Example of the problem you can see an what I want. Given a set of points (blue dots) I want to find the largest convex polygon that can be fit inside the 'hole' in this clound of points that also contains my given arbitrary point (red dot). The result should be something similar to this.
I managed to solve this by applying a transformation in my original dataset to transform it inside-out, applying the convex-hull algorithm, and applying the counter-transformation to the result to retrieve the inner convex hull. This work as long as my hole well-behaved (i.e. convex and minor eccentricity). If I aaply it to a non-convex hole, it gives me very weird results.
What I am looking for is any literature that can help me with this problem.