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authorBrian Paul <[email protected]>2001-03-17 00:25:40 +0000
committerBrian Paul <[email protected]>2001-03-17 00:25:40 +0000
commit77cc447b96a75106354da02437c4e868265d27bb (patch)
tree06336e071d4786d72d681c72d68126191f0b2993 /src/glu/sgi/libtess/alg-outline
parent24fab8e2507d9ccc45c1a94de0ad44088cfb8738 (diff)
SGI SI GLU library
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+/*
+** $Header: /home/krh/git/sync/mesa-cvs-repo/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.