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Вы можете ознакомиться и скачать презентацию на тему Drawing triangles. Доклад-сообщение содержит 32 слайдов. Презентации для любого класса можно скачать бесплатно. Если материал и наш сайт презентаций Mypresentation Вам понравились – поделитесь им с друзьями с помощью социальных кнопок и добавьте в закладки в своем браузере.

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Drawing Triangles CS 445/645 Introduction to Computer Graphics David Luebke, Spring 2003

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Admin Homework 1 graded, will post this afternoon

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Rasterizing Polygons In interactive graphics, polygons rule the world Two main reasons: Lowest common denominator for surfaces Can represent any surface with arbitrary accuracy Splines, mathematical functions, volumetric isosurfaces… Mathematical simplicity lends itself to simple, regular rendering algorithms Like those we’re about to discuss… Such algorithms embed well in hardware

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Rasterizing Polygons Triangle is the minimal unit of a polygon All polygons can be broken up into triangles Convex, concave, complex Triangles are guaranteed to be: Planar Convex What exactly does it mean to be convex?

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Convex Shapes A two-dimensional shape is convex if and only if every line segment connecting two points on the boundary is entirely contained.

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Convex Shapes Why do we want convex shapes for rasterization? One good answer: because any scan line is guaranteed to contain at most one segment or span of a triangle Another answer coming up later Note: Can also use an algorithm which handles concave polygons. It is more complex than what we’ll present here!

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Decomposing Polys Into Tris Any convex polygon can be trivially decomposed into triangles Draw it Any concave or complex polygon can be decomposed into triangles, too Non-trivial!

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Rasterizing Triangles Interactive graphics hardware commonly uses edge walking or edge equation techniques for rasterizing triangles Two techniques we won’t talk about much: Recursive subdivision of primitive into micropolygons (REYES, Renderman) Recursive subdivision of screen (Warnock)

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Recursive Triangle Subdivision

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Recursive Screen Subdivision

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Edge Walking Basic idea: Draw edges vertically Fill in horizontal spans for each scanline Interpolate colors down edges At each scanline, interpolate edge colors across span

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Edge Walking: Notes Order vertices in x and y 3 cases: break left, break right, no break Walk down left and right edges Fill each span Until breakpoint or bottom vertex is reached Advantage: can be made very fast Disadvantages: Lots of finicky special cases Tough to get right Need to pay attention to fractional offsets

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Edge Walking: Notes Fractional offsets: Be careful when interpolating color values! Also: beware gaps between adjacent edges

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Edge Equations An edge equation is simply the equation of the line containing that edge Q: What is the equation of a 2D line? A: Ax + By + C = 0 Q: Given a point (x,y), what does plugging x & y into this equation tell us? A: Whether the point is: On the line: Ax + By + C = 0 “Above” the line: Ax + By + C > 0 “Below” the line: Ax + By + C < 0

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Edge Equations Edge equations thus define two half-spaces:

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Edge Equations And a triangle can be defined as the intersection of three positive half-spaces:

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Edge Equations So…simply turn on those pixels for which all edge equations evaluate to > 0:

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Using Edge Equations An aside: How do you suppose edge equations are implemented in hardware? How would you implement an edge-equation rasterizer in software? Which pixels do you consider? How do you compute the edge equations? How do you orient them correctly?

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Using Edge Equations Which pixels: compute min,max bounding box Edge equations: compute from vertices Orientation: ensure area is positive (why?)

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Computing a Bounding Box Easy to do Surprising number of speed hacks possible See McMillan’s Java code for an example

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Computing Edge Equations Want to calculate A, B, C for each edge from (xi, yi) and (xj, yj) Treat it as a linear system: Ax1 + By1 + C = 0 Ax2 + By2 + C = 0 Notice: two equations, three unknowns Does this make sense? What can we solve? Goal: solve for A & B in terms of C

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Computing Edge Equations Set up the linear system: Multiply both sides by matrix inverse: Let C = x0 y1 - x1 y0 for convenience Then A = y0 - y1 and B = x1 - x0

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Computing Edge Equations: Numerical Issues Calculating C = x0 y1 - x1 y0 involves some numerical precision issues When is it bad to subtract two floating-point numbers? A: When they are of similar magnitude Example: 1.234x104 - 1.233x104 = 1.000x101 We lose most of the significant digits in result In general, (x0,y0) and (x1,y1) (corner vertices of a triangle) are fairly close, so we have a problem

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Computing Edge Equations: Numerical Issues We can avoid the problem in this case by using our definitions of A and B: A = y0 - y1 B = x1 - x0 C = x0 y1 - x1 y0 Thus: C = -Ax0 - By0 or C = -Ax1 - By1 Why is this better? Which should we choose? Trick question! Average the two to avoid bias: C = -[A(x0+x1) + B(y0+y1)] / 2

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Edge Equations So…we can find edge equation from two verts. Given three corners C0, C1, C0 of a triangle, what are our three edges? How do we make sure the half-spaces defined by the edge equations all share the same sign on the interior of the triangle? A: Be consistent (Ex: [C0 C1], [C1 C2], [C2 C0]) How do we make sure that sign is positive? A: Test, and flip if needed (A= -A, B= -B, C= -C)

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Edge Equations: Code Basic structure of code: Setup: compute edge equations, bounding box (Outer loop) For each scanline in bounding box... (Inner loop) …check each pixel on scanline, evaluating edge equations and drawing the pixel if all three are positive

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Optimize This! findBoundingBox(&xmin, &xmax, &ymin, &ymax); setupEdges (&a0,&b0,&c0,&a1,&b1,&c1,&a2,&b2,&c2); /* Optimize this: */ for (int y = yMin; y 0 && e2 > 0) setPixel(x,y); } }

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Edge Equations: Speed Hacks Some speed hacks for the inner loop: int xflag = 0; for (int x = xMin; x 0) { setPixel(x,y); xflag++; } else if (xflag != 0) break; e0 += a0; e1 += a1; e2 += a2; } Incremental update of edge equation values (think DDA) Early termination (why does this work?) Faster test of equation values

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Edge Equations: Interpolating Color Given colors (and later, other parameters) at the vertices, how to interpolate across? Idea: triangles are planar in any space: This is the “redness” parameter space Note:plane follows form z = Ax + By + C Look familiar?

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Edge Equations: Interpolating Color Given redness at the 3 vertices, set up the linear system of equations: The solution works out to:

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Edge Equations: Interpolating Color Notice that the columns in the matrix are exactly the coefficients of the edge equations! So the setup cost per parameter is basically a matrix multiply Per-pixel cost (the inner loop) cost equates to tracking another edge equation value

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Triangle Rasterization Issues Exactly which pixels should be lit? A: Those pixels inside the triangle edges What about pixels exactly on the edge? (Ex.) Draw them: order of triangles matters (it shouldn’t) Don’t draw them: gaps possible between triangles We need a consistent (if arbitrary) rule Example: draw pixels on left or top edge, but not on right or bottom edge

Теги Drawing triangles

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