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In computational geometry, the smallest enclosing box problem is that of finding the oriented minimum bounding box enclosing a set of points. It is a type of bounding volume. "Smallest" may refer to volume, area, perimeter, etc. of the box. It is sufficient to find the smallest enclosing box for the convex hull of the objects in question. It is ...
A sphere enclosed by its axis-aligned minimum bounding box (in 3 dimensions) In geometry, the minimum bounding box or smallest bounding box (also known as the minimum enclosing box or smallest enclosing box) for a point set S in N dimensions is the box with the smallest measure (area, volume, or hypervolume in higher dimensions) within which all the points lie.
One of O'Rourke's early results was an algorithm for finding the minimum bounding box of a point set in three dimensions when the box is not required to be axis-aligned. The problem is made difficult by the fact that the optimal box may not share any of its face planes with the convex hull of the point set.
A series of geometric shapes enclosed by its minimum bounding rectangle. In computational geometry, the minimum bounding rectangle (MBR), also known as bounding box (BBOX) or envelope, is an expression of the maximum extents of a two-dimensional object (e.g. point, line, polygon) or set of objects within its x-y coordinate system; in other words min(x), max(x), min(y), max(y).
2-D case: Smallest bounding rectangle (Smallest enclosing rectangle) There are two common variants of this problem. In many areas of computer graphics, the bounding box (often abbreviated to bbox) is understood to be the smallest box delimited by sides parallel to coordinate axes which encloses the objects in question.
It is minimal if for all boxes [x], we have ([]) = [[]], where [A] is the interval hull of the set A, i.e., the smallest box enclosing A. The contractor C is thin if for all points x , C ( { x } ) = { x } ∩ X {\displaystyle C(\{x\})=\{x\}\cap X} where { x } denotes the degenerated box enclosing x as a single point.
Packing different rectangles in a rectangle: The problem of packing multiple rectangles of varying widths and heights in an enclosing rectangle of minimum area (but with no boundaries on the enclosing rectangle's width or height) has an important application in combining images into a single larger image. A web page that loads a single larger ...
The algorithm selects one point p randomly and uniformly from P, and recursively finds the minimal circle containing P – {p}, i.e. all of the other points in P except p. If the returned circle also encloses p, it is the minimal circle for the whole of P and is returned. Otherwise, point p must lie on the boundary of the result circle.