658e102f32be743bb1082c4ba9b9faeac0652ce8
[reactos.git] / reactos / dll / glu32 / libtess / alg-outline
1 /*
2 ** $Header: /cygdrive/c/RCVS/CVS/ReactOS/reactos/lib/glu32/libtess/alg-outline,v 1.1 2004/02/02 16:39:15 navaraf Exp $
3 */
4
5 This is only a very brief overview. There is quite a bit of
6 additional documentation in the source code itself.
7
8
9 Goals of robust tesselation
10 ---------------------------
11
12 The tesselation algorithm is fundamentally a 2D algorithm. We
13 initially project all data into a plane; our goal is to robustly
14 tesselate the projected data. The same topological tesselation is
15 then applied to the input data.
16
17 Topologically, the output should always be a tesselation. If the
18 input is even slightly non-planar, then some triangles will
19 necessarily be back-facing when viewed from some angles, but the goal
20 is to minimize this effect.
21
22 The algorithm needs some capability of cleaning up the input data as
23 well as the numerical errors in its own calculations. One way to do
24 this is to specify a tolerance as defined above, and clean up the
25 input and output during the line sweep process. At the very least,
26 the algorithm must handle coincident vertices, vertices incident to an
27 edge, and coincident edges.
28
29
30 Phases of the algorithm
31 -----------------------
32
33 1. Find the polygon normal N.
34 2. Project the vertex data onto a plane. It does not need to be
35 perpendicular to the normal, eg. we can project onto the plane
36 perpendicular to the coordinate axis whose dot product with N
37 is largest.
38 3. Using a line-sweep algorithm, partition the plane into x-monotone
39 regions. Any vertical line intersects an x-monotone region in
40 at most one interval.
41 4. Triangulate the x-monotone regions.
42 5. Group the triangles into strips and fans.
43
44
45 Finding the normal vector
46 -------------------------
47
48 A common way to find a polygon normal is to compute the signed area
49 when the polygon is projected along the three coordinate axes. We
50 can't do this, since contours can have zero area without being
51 degenerate (eg. a bowtie).
52
53 We fit a plane to the vertex data, ignoring how they are connected
54 into contours. Ideally this would be a least-squares fit; however for
55 our purpose the accuracy of the normal is not important. Instead we
56 find three vertices which are widely separated, and compute the normal
57 to the triangle they form. The vertices are chosen so that the
58 triangle has an area at least 1/sqrt(3) times the largest area of any
59 triangle formed using the input vertices.
60
61 The contours do affect the orientation of the normal; after computing
62 the normal, we check that the sum of the signed contour areas is
63 non-negative, and reverse the normal if necessary.
64
65
66 Projecting the vertices
67 -----------------------
68
69 We project the vertices onto a plane perpendicular to one of the three
70 coordinate axes. This helps numerical accuracy by removing a
71 transformation step between the original input data and the data
72 processed by the algorithm. The projection also compresses the input
73 data; the 2D distance between vertices after projection may be smaller
74 than the original 2D distance. However by choosing the coordinate
75 axis whose dot product with the normal is greatest, the compression
76 factor is at most 1/sqrt(3).
77
78 Even though the *accuracy* of the normal is not that important (since
79 we are projecting perpendicular to a coordinate axis anyway), the
80 *robustness* of the computation is important. For example, if there
81 are many vertices which lie almost along a line, and one vertex V
82 which is well-separated from the line, then our normal computation
83 should involve V otherwise the results will be garbage.
84
85 The advantage of projecting perpendicular to the polygon normal is
86 that computed intersection points will be as close as possible to
87 their ideal locations. To get this behavior, define TRUE_PROJECT.
88
89
90 The Line Sweep
91 --------------
92
93 There are three data structures: the mesh, the event queue, and the
94 edge dictionary.
95
96 The mesh is a "quad-edge" data structure which records the topology of
97 the current decomposition; for details see the include file "mesh.h".
98
99 The event queue simply holds all vertices (both original and computed
100 ones), organized so that we can quickly extract the vertex with the
101 minimum x-coord (and among those, the one with the minimum y-coord).
102
103 The edge dictionary describes the current intersection of the sweep
104 line with the regions of the polygon. This is just an ordering of the
105 edges which intersect the sweep line, sorted by their current order of
106 intersection. For each pair of edges, we store some information about
107 the monotone region between them -- these are call "active regions"
108 (since they are crossed by the current sweep line).
109
110 The basic algorithm is to sweep from left to right, processing each
111 vertex. The processed portion of the mesh (left of the sweep line) is
112 a planar decomposition. As we cross each vertex, we update the mesh
113 and the edge dictionary, then we check any newly adjacent pairs of
114 edges to see if they intersect.
115
116 A vertex can have any number of edges. Vertices with many edges can
117 be created as vertices are merged and intersection points are
118 computed. For unprocessed vertices (right of the sweep line), these
119 edges are in no particular order around the vertex; for processed
120 vertices, the topological ordering should match the geometric ordering.
121
122 The vertex processing happens in two phases: first we process are the
123 left-going edges (all these edges are currently in the edge
124 dictionary). This involves:
125
126 - deleting the left-going edges from the dictionary;
127 - relinking the mesh if necessary, so that the order of these edges around
128 the event vertex matches the order in the dictionary;
129 - marking any terminated regions (regions which lie between two left-going
130 edges) as either "inside" or "outside" according to their winding number.
131
132 When there are no left-going edges, and the event vertex is in an
133 "interior" region, we need to add an edge (to split the region into
134 monotone pieces). To do this we simply join the event vertex to the
135 rightmost left endpoint of the upper or lower edge of the containing
136 region.
137
138 Then we process the right-going edges. This involves:
139
140 - inserting the edges in the edge dictionary;
141 - computing the winding number of any newly created active regions.
142 We can compute this incrementally using the winding of each edge
143 that we cross as we walk through the dictionary.
144 - relinking the mesh if necessary, so that the order of these edges around
145 the event vertex matches the order in the dictionary;
146 - checking any newly adjacent edges for intersection and/or merging.
147
148 If there are no right-going edges, again we need to add one to split
149 the containing region into monotone pieces. In our case it is most
150 convenient to add an edge to the leftmost right endpoint of either
151 containing edge; however we may need to change this later (see the
152 code for details).
153
154
155 Invariants
156 ----------
157
158 These are the most important invariants maintained during the sweep.
159 We define a function VertLeq(v1,v2) which defines the order in which
160 vertices cross the sweep line, and a function EdgeLeq(e1,e2; loc)
161 which says whether e1 is below e2 at the sweep event location "loc".
162 This function is defined only at sweep event locations which lie
163 between the rightmost left endpoint of {e1,e2}, and the leftmost right
164 endpoint of {e1,e2}.
165
166 Invariants for the Edge Dictionary.
167
168 - Each pair of adjacent edges e2=Succ(e1) satisfies EdgeLeq(e1,e2)
169 at any valid location of the sweep event.
170 - If EdgeLeq(e2,e1) as well (at any valid sweep event), then e1 and e2
171 share a common endpoint.
172 - For each e in the dictionary, e->Dst has been processed but not e->Org.
173 - Each edge e satisfies VertLeq(e->Dst,event) && VertLeq(event,e->Org)
174 where "event" is the current sweep line event.
175 - No edge e has zero length.
176 - No two edges have identical left and right endpoints.
177
178 Invariants for the Mesh (the processed portion).
179
180 - The portion of the mesh left of the sweep line is a planar graph,
181 ie. there is *some* way to embed it in the plane.
182 - No processed edge has zero length.
183 - No two processed vertices have identical coordinates.
184 - Each "inside" region is monotone, ie. can be broken into two chains
185 of monotonically increasing vertices according to VertLeq(v1,v2)
186 - a non-invariant: these chains may intersect (slightly) due to
187 numerical errors, but this does not affect the algorithm's operation.
188
189 Invariants for the Sweep.
190
191 - If a vertex has any left-going edges, then these must be in the edge
192 dictionary at the time the vertex is processed.
193 - If an edge is marked "fixUpperEdge" (it is a temporary edge introduced
194 by ConnectRightVertex), then it is the only right-going edge from
195 its associated vertex. (This says that these edges exist only
196 when it is necessary.)
197
198
199 Robustness
200 ----------
201
202 The key to the robustness of the algorithm is maintaining the
203 invariants above, especially the correct ordering of the edge
204 dictionary. We achieve this by:
205
206 1. Writing the numerical computations for maximum precision rather
207 than maximum speed.
208
209 2. Making no assumptions at all about the results of the edge
210 intersection calculations -- for sufficiently degenerate inputs,
211 the computed location is not much better than a random number.
212
213 3. When numerical errors violate the invariants, restore them
214 by making *topological* changes when necessary (ie. relinking
215 the mesh structure).
216
217
218 Triangulation and Grouping
219 --------------------------
220
221 We finish the line sweep before doing any triangulation. This is
222 because even after a monotone region is complete, there can be further
223 changes to its vertex data because of further vertex merging.
224
225 After triangulating all monotone regions, we want to group the
226 triangles into fans and strips. We do this using a greedy approach.
227 The triangulation itself is not optimized to reduce the number of
228 primitives; we just try to get a reasonable decomposition of the
229 computed triangulation.