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authorDavid Nusinow <[email protected]>2005-12-30 20:12:45 +0000
committerDavid Nusinow <[email protected]>2005-12-30 20:12:45 +0000
commitbda1e332ce5efe2057421dec58202b43707a504c (patch)
tree4b825dc642cb6eb9a060e54bf8d69288fbee4904 /src/glu/sgi/libtess/alg-outline
parent53b2ad5fd0aaff8cbd605d337b862f12debb26cb (diff)
Update libs to 7.0 release with packaging
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-/*
-** $Header: /cvs/mesa/Mesa/src/glu/sgi/libtess/alg-outline,v 1.1 2001/03/17 00:25:41 brianp Exp $
-*/
-
-This is only a very brief overview. There is quite a bit of
-additional documentation in the source code itself.
-
-
-Goals of robust tesselation
----------------------------
-
-The tesselation algorithm is fundamentally a 2D algorithm. We
-initially project all data into a plane; our goal is to robustly
-tesselate the projected data. The same topological tesselation is
-then applied to the input data.
-
-Topologically, the output should always be a tesselation. If the
-input is even slightly non-planar, then some triangles will
-necessarily be back-facing when viewed from some angles, but the goal
-is to minimize this effect.
-
-The algorithm needs some capability of cleaning up the input data as
-well as the numerical errors in its own calculations. One way to do
-this is to specify a tolerance as defined above, and clean up the
-input and output during the line sweep process. At the very least,
-the algorithm must handle coincident vertices, vertices incident to an
-edge, and coincident edges.
-
-
-Phases of the algorithm
------------------------
-
-1. Find the polygon normal N.
-2. Project the vertex data onto a plane. It does not need to be
- perpendicular to the normal, eg. we can project onto the plane
- perpendicular to the coordinate axis whose dot product with N
- is largest.
-3. Using a line-sweep algorithm, partition the plane into x-monotone
- regions. Any vertical line intersects an x-monotone region in
- at most one interval.
-4. Triangulate the x-monotone regions.
-5. Group the triangles into strips and fans.
-
-
-Finding the normal vector
--------------------------
-
-A common way to find a polygon normal is to compute the signed area
-when the polygon is projected along the three coordinate axes. We
-can't do this, since contours can have zero area without being
-degenerate (eg. a bowtie).
-
-We fit a plane to the vertex data, ignoring how they are connected
-into contours. Ideally this would be a least-squares fit; however for
-our purpose the accuracy of the normal is not important. Instead we
-find three vertices which are widely separated, and compute the normal
-to the triangle they form. The vertices are chosen so that the
-triangle has an area at least 1/sqrt(3) times the largest area of any
-triangle formed using the input vertices.
-
-The contours do affect the orientation of the normal; after computing
-the normal, we check that the sum of the signed contour areas is
-non-negative, and reverse the normal if necessary.
-
-
-Projecting the vertices
------------------------
-
-We project the vertices onto a plane perpendicular to one of the three
-coordinate axes. This helps numerical accuracy by removing a
-transformation step between the original input data and the data
-processed by the algorithm. The projection also compresses the input
-data; the 2D distance between vertices after projection may be smaller
-than the original 2D distance. However by choosing the coordinate
-axis whose dot product with the normal is greatest, the compression
-factor is at most 1/sqrt(3).
-
-Even though the *accuracy* of the normal is not that important (since
-we are projecting perpendicular to a coordinate axis anyway), the
-*robustness* of the computation is important. For example, if there
-are many vertices which lie almost along a line, and one vertex V
-which is well-separated from the line, then our normal computation
-should involve V otherwise the results will be garbage.
-
-The advantage of projecting perpendicular to the polygon normal is
-that computed intersection points will be as close as possible to
-their ideal locations. To get this behavior, define TRUE_PROJECT.
-
-
-The Line Sweep
---------------
-
-There are three data structures: the mesh, the event queue, and the
-edge dictionary.
-
-The mesh is a "quad-edge" data structure which records the topology of
-the current decomposition; for details see the include file "mesh.h".
-
-The event queue simply holds all vertices (both original and computed
-ones), organized so that we can quickly extract the vertex with the
-minimum x-coord (and among those, the one with the minimum y-coord).
-
-The edge dictionary describes the current intersection of the sweep
-line with the regions of the polygon. This is just an ordering of the
-edges which intersect the sweep line, sorted by their current order of
-intersection. For each pair of edges, we store some information about
-the monotone region between them -- these are call "active regions"
-(since they are crossed by the current sweep line).
-
-The basic algorithm is to sweep from left to right, processing each
-vertex. The processed portion of the mesh (left of the sweep line) is
-a planar decomposition. As we cross each vertex, we update the mesh
-and the edge dictionary, then we check any newly adjacent pairs of
-edges to see if they intersect.
-
-A vertex can have any number of edges. Vertices with many edges can
-be created as vertices are merged and intersection points are
-computed. For unprocessed vertices (right of the sweep line), these
-edges are in no particular order around the vertex; for processed
-vertices, the topological ordering should match the geometric ordering.
-
-The vertex processing happens in two phases: first we process are the
-left-going edges (all these edges are currently in the edge
-dictionary). This involves:
-
- - deleting the left-going edges from the dictionary;
- - relinking the mesh if necessary, so that the order of these edges around
- the event vertex matches the order in the dictionary;
- - marking any terminated regions (regions which lie between two left-going
- edges) as either "inside" or "outside" according to their winding number.
-
-When there are no left-going edges, and the event vertex is in an
-"interior" region, we need to add an edge (to split the region into
-monotone pieces). To do this we simply join the event vertex to the
-rightmost left endpoint of the upper or lower edge of the containing
-region.
-
-Then we process the right-going edges. This involves:
-
- - inserting the edges in the edge dictionary;
- - computing the winding number of any newly created active regions.
- We can compute this incrementally using the winding of each edge
- that we cross as we walk through the dictionary.
- - relinking the mesh if necessary, so that the order of these edges around
- the event vertex matches the order in the dictionary;
- - checking any newly adjacent edges for intersection and/or merging.
-
-If there are no right-going edges, again we need to add one to split
-the containing region into monotone pieces. In our case it is most
-convenient to add an edge to the leftmost right endpoint of either
-containing edge; however we may need to change this later (see the
-code for details).
-
-
-Invariants
-----------
-
-These are the most important invariants maintained during the sweep.
-We define a function VertLeq(v1,v2) which defines the order in which
-vertices cross the sweep line, and a function EdgeLeq(e1,e2; loc)
-which says whether e1 is below e2 at the sweep event location "loc".
-This function is defined only at sweep event locations which lie
-between the rightmost left endpoint of {e1,e2}, and the leftmost right
-endpoint of {e1,e2}.
-
-Invariants for the Edge Dictionary.
-
- - Each pair of adjacent edges e2=Succ(e1) satisfies EdgeLeq(e1,e2)
- at any valid location of the sweep event.
- - If EdgeLeq(e2,e1) as well (at any valid sweep event), then e1 and e2
- share a common endpoint.
- - For each e in the dictionary, e->Dst has been processed but not e->Org.
- - Each edge e satisfies VertLeq(e->Dst,event) && VertLeq(event,e->Org)
- where "event" is the current sweep line event.
- - No edge e has zero length.
- - No two edges have identical left and right endpoints.
-
-Invariants for the Mesh (the processed portion).
-
- - The portion of the mesh left of the sweep line is a planar graph,
- ie. there is *some* way to embed it in the plane.
- - No processed edge has zero length.
- - No two processed vertices have identical coordinates.
- - Each "inside" region is monotone, ie. can be broken into two chains
- of monotonically increasing vertices according to VertLeq(v1,v2)
- - a non-invariant: these chains may intersect (slightly) due to
- numerical errors, but this does not affect the algorithm's operation.
-
-Invariants for the Sweep.
-
- - If a vertex has any left-going edges, then these must be in the edge
- dictionary at the time the vertex is processed.
- - If an edge is marked "fixUpperEdge" (it is a temporary edge introduced
- by ConnectRightVertex), then it is the only right-going edge from
- its associated vertex. (This says that these edges exist only
- when it is necessary.)
-
-
-Robustness
-----------
-
-The key to the robustness of the algorithm is maintaining the
-invariants above, especially the correct ordering of the edge
-dictionary. We achieve this by:
-
- 1. Writing the numerical computations for maximum precision rather
- than maximum speed.
-
- 2. Making no assumptions at all about the results of the edge
- intersection calculations -- for sufficiently degenerate inputs,
- the computed location is not much better than a random number.
-
- 3. When numerical errors violate the invariants, restore them
- by making *topological* changes when necessary (ie. relinking
- the mesh structure).
-
-
-Triangulation and Grouping
---------------------------
-
-We finish the line sweep before doing any triangulation. This is
-because even after a monotone region is complete, there can be further
-changes to its vertex data because of further vertex merging.
-
-After triangulating all monotone regions, we want to group the
-triangles into fans and strips. We do this using a greedy approach.
-The triangulation itself is not optimized to reduce the number of
-primitives; we just try to get a reasonable decomposition of the
-computed triangulation.