Description
In the last assignment, you have make a great achievement to move a model to screen. This
time, you will dig deeply into the rasterization! Basically, this project has 6 tasks, worth a total
130 points (30 extra points can be added if you completed a fancy additional work). The tasks are
as follows:
• Draw a single color triangles (20 points + 10 extra)
• Antialiasing (20 points + 10 extra)
• Transforms (10 points)
• Barycentric coordinate (10 points)
• Barycentric coordinate (10 points)
• Texture mapping (10 points)
• Mipmapping(30 points) (10 extra included if you complete well)
The goals of your write-up are for you to (a) think about and articulate what you’ve built and
learned in your own words, (b) have a write-up of the project to take away from the class. Your
write-up should include:
• An overview of the project, your approach to and implementation for each of the parts, and
what problems you encountered and how you solved them. Strive for clarity and succinctness.
• On each part, make sure to include the results described in the corresponding Deliverables
section in addition to your explanation. If you failed to generate any results correctly, provide
a brief explanation of why.
• The final (optional) part for the art competition is where you have the opportunity to be
creative and individual, so be sure to provide a good description of what you were going for
and how you implemented it.
• Clearly indicate any extra credit items you completed, and provide a thorough explanation
and illustration for each of them.
The write-up is one of our main methods of evaluating your work, so it is important to spend
the time to do it correctly and thoroughly. Plan ahead to allocate time for the write-up well before
the deadline.
Note, before you start to do assignment, install OpenGL using the following command:
21$sudo apt update
2$sudo apt i n s t a l l f r e e g l u t 3 -dev
3$sudo apt i n s t a l l freetype6 -dev
4$sudo apt i n s t a l l xorg – dec l i b g l u 1 -mesa-dev
After compiling, you will get a ”draw” executable file. use it to run the given .svg files.
1
Draw a single color triangles (20 points)
Implement the function rasterize_triangle function in rasterizer.cpp.
You should:
• For each pixel, perform the point-in-triangle tests with a sample point in the center of the
pixel. Sample coordinates = the integer point + (.5,.5).
• In task 2, you will implement sub-pixel supersampling, but here you should just sample once
per pixel and call the f ill_pixel() helper function. Follow the example in the rasterize_point
function in the starter code.
• Your implementation should assume that a sample on the boundary of the triangle is to be
drawn. Do make sure that none of your edges are left un-rasterized.
• Your implementation should be at least as efficient as sampling only within the bounding
box of the triangle (not simply every pixel in the framebuffer).
• Your code should draw the triangle regardless of the winding order of the vertices (i.e. clock-
wise or counter-clockwise). Check svg/basic/test6.svg.
When finished, you should be able to render test SVG files with single-color polygons (which are
triangulated into triangles elsewhere in the code before being passed to your function. Complete
the given function in rasterizer.cpp.
1RasterizerImp :: r a s t e r i z e _ t r i a n g l e ()
2Antialiasing (20 points)
Use supersampling to antialias your triangles. The sample_rate parameter in DrawRend
(adjusted using the − and = keys) tells you how many samples to use per pixel.
Figure 2 shows how sampling four times per pixel produces a better result than just sampling
once. The fraction of the supersamples within the triangle yields a smoother edge.
3Figure 1: Supersampling
Sample at sqrt(sample_rate) ∗ sqrt(sampler ate) grid locations distributed over the pixel area.
(sample_rate is a member variable of the RasterizerImp class)
One reasonable way to think about supersampling is simply rasterizing an image that is higher
resolution, then downsampling the higher resolution image to the output resolution of the frame-
buffer.
The original f ilp ixel function used in Task 1 directly draws onto the framebuffer, but for super-
sampling, you should draw into the sample_buf f er first, filling all the subsamples corresponding
to the output pixel.
To reiterate the overall pipeline of the rasterizer:
• SV GP arser parses the svg file into SVG class representation.
• When rasterization starts, the renderer (DrawRend :: redraw) calls SV G :: draw.
• SV G :: draw calls the specific line / triangle / point rasterization functions to generate the
image primitive by primitive.
• DrawRend :: redraw calls line rasterization to draw the square boundary.
• DrawRend :: redraw calls RasterizerImp :: resolvet of ramebuf f er() to translate the inter-
nal buffer of the rasterizer to the screenbuffer so the image can be displayed and written into
a file.
To manage the memory for supersampled data, use the RasterizerImp :: sampleb uf f er vector
(see file rasterizer.h) for this purpose. It depends on your algorithm, but it is likely that the size
4of the sample buffer you need will depend on the framebuffer dimensions (which changes when
the window is resized) and the supersampling rate (which changes with keystrokes as described
above). You will need to update the size of the buffer dynamically. There are hints below and
in the code for where you may want to manage the size of your buffer.
• Clear the values in your sample buffer memory and/or framebuffer appropriately at the
beginning of redrawing the frame. This is erasing the frame before you start drawing.
• Update your rasterize_triangle function to perform supersampling into your supersample
buffer memory. (If you implement it with no extra memory, you will get 10 more points.
Memory consumed no more than the size of the image. Explain what you did and what’s
the trade-off in your report).
• At the end of rasterizing all the scene elements, you will need to populate the framebuffer
from your supersamples. This is sometimes called resolving the samples into the framebuffer.
Notice that the RasterizerImp :: resolvet of ramebuf f er function is called as the last step
in rendering the frame in drawrend.cpp, so you may wish to implement this part of your
algorithm here.
• Note that you will need to convert between different color datatypes. RasterizerImp ::
rgbf ramebuf f ert arget stores a pointer to the framebuffer pixel data that is finally drawn
to the display. rgbf ramebuf f ert arget is an array of 8-bit values for each of the R, G and
B components of each pixel’s color – this is the compact data format expected by most real
graphics systems for drawing to the display. In contrast, the RasterizerImp :: sampleb uf f er
variable that we suggest you use for your supersample memory is an array of Color objects
that store R, G and B internally as floating point values. You may wish to familiarize
yourself with the Color class. You may need to convert between these datatypes. Watch out
for floating point to integer conversion errors, such as rounding and overflow.
• You will likely find that points and lines stop rendering correctly after your supersampling
modifications. Lines and points are not supersampled, but they still need to be drawn into
the supersample buffer. Modify RasterizerImp :: f illp ixel if needed to restore functionality.
One way to think about this is to fill all the supersamples corresponding to the point or line
with the same color, so it comes out as a single sampled pixel in the framebuffer. You do
NOT need to antialias points and lines.
Complete or use the given functions.
1\\ For managing supersample buffer memory
2\\ in
rasterizer . h
and
rasterizer . cpp
53RasterizerImp :: r a s t e r i z e _ t r i a n g l e ()
4RasterizerImp :: set_sample_rate ()
5RasterizerImp :: set_framebuffer_target ()
6RasterizerImp :: c l e a r _ b u f f e r s ()
7
8\\ To implement triangle supersampling
9RasterizerImp :: r a s t e r i z e _ t r i a n g l e ()
10RasterizerImp :: f i l l _ p i x e l ()
rasterizer . cpp
11
12\\ For resolving supersamples to framebuffer
13RasterizerImp :: resolve_to_framebuffer ()
3Transforms (10 points)
Implement the three transforms in the transforms.cpp file according to the SV G spec. The
matrices are 3×3 because they operate in homogeneous coordinates – you can see how they will be
used on instances of Vector2D by looking at the way the * operator is overloaded in the same file.
Once you’ve implemented these transforms, svg/transf orms/robot.svg should render correctly,
as follows:
Figure 2: Texture map (left) and Transform(right)
Complete the given functions.
1t r a n s l a t e ()
2s c a l e ()
3r o t a t e ()
64
Barycentric coordinates (10 points)
Implement RasterizerImp :: rasterizei nterpolatedc olort riangle(…) to draw a triangle with
colors defined at the vertices and interpolated across the triangle area using barycentric interpola-
tion.
Once done, you should be able to see a color wheel in svg/basic/test7.svg(below, right).
Complete the given functions.
1
RasterizerImp :: r a s t e r i z e _ i n t e r p o l a t e d _ c o l o r _ t r i a n g l e (…)
Figure 3: transform
5
Pixel sampling for texture mapping (10 points)
Implement RasterizerImp :: rasterize_texturedt riangle(…) to draw a triangle with colors
defined by texture mapping with the given 2D texture coordinates at each vertex and the given
Texture image. Here you will implement texture sampling on the full-resolution texture image
using nearest neighbor and bilinear interpolation, as described in lecture.
The GUI toggles RasterizerImp’s P ixelSampleM ethod variable psm using the ’P’ key. When
psm == P _N EAREST , you should use nearest-pixel sampling, and when psm == P _LIN EAR,
you should use bilinear sampling. Please do so by implementing T exture :: samplen earest and
T exture :: sampleb ilinear functions and calling them from RasterizerImp :: rasterize_texturedt riangle(…).
This approach will allow you to reuse these functions for trilinear texture filtering in Task 6.
Now you should be able to rasterize the svg files in svg/texmap/, which rely on texture maps.
Hints:
• The T exture struct in texture.h stores a mipmap, as described in lecture, of texture images
in decreasing resolution, in the mipmap variable. Each texture image is stored as an object
of type M ipLevel.
7• M ipLevel :: texels stores the texture image pixels in the typical RGB format described above
for framebuffer pixels.
• M ipLevel :: get_texel(…) may be helpful.
• At this part of the project, you haven’t implemented level sampling (mip-mapping) yet, so
the program should default to zero-th level (full resolution).
Complete the given functions.
1RasterizerImp :: rasterize_textured_triangle ()
2Texture :: sample_nearest ()
3Texture :: sample_bilinear ()
6Mipmapping (20 Points)
Continue with the last task.
Update RasterizerImp :: rasterize_textured_triangle(…)
to support sampling different mipmap levels (M ipLevel S). The GUI toggles RasterizerImp’s
LevelSampleM ethod variable lsm using the L key. Implement the following level sampling meth-
ods in the helper function T exture :: sample.
• When lsm == L_ZERO, you should sample from the zero-th MipLevel, as in Part 5.
• When lsm == L_N EAREST , you should compute the nearest appropriate mipmap level
and pass that level as a parameter to the nearest or bilinear sample function.
• When lsm == L_LIN EAR, you should compute the mipmap level as a continuous number.
Then compute a weighted sum of using one sample from each of the adjacent mipmap levels
as described in lecture.
dv
In addition, implement T exture :: getl evel as a helper function. You will need ( du
dx , dx )and
dv
( du
dy , dy ) to calculate the correct mipmap level. In order to get these values corresponding to a
point (x,y)(x,y) inside a triangle, you must perform the following.
• Calculate the uv barycentric coordinates of (x,y)(x,y), (x+1,y)(x+1,y), and (x,y+1)(x,y+1)
in rasterize_textured_triangle(…) as sp.p_uv, sp.p_dx_uv, and sp.p_dy_uv, assign them
to a SampleP arams struct sp, along with other values required by the struct, and pass sp
to T exture :: get_level
• Calculate the difference vectors sp.p_dxu v − sp.p_uv and sp.p_dy_uv − sp.p_uv inside
T exture :: get_level, and finally
8• Scale up the difference vectors accordingly by the width and height of the full-resolution
texture image.
With these, you can proceed with the calculation from the lecture slides.
Notes:
• The lsm and psm variables can be set independently and interacted independently. In other
words, all combinations of psm == [P _N EAREST, PL IN EAR]×lsm == [LZ ERO, L_N EAREST, L_LIN E
are valid.
• When lsm == L_LIN EAR and psm == P _LIN EAR, this is known as trilinear sampling,
or trilinear texture filtering, as described in lecture.
• You may find it helpful to visualize what parts of the image use different levels of the mipmap.
One way to do this is by normalizing the value returned by T exture :: getl evel by the
maximum level (i.e. size of the mipmap) and have that value returned by T exture :: sample
as a color. Zoom in and out of the image to see how the levels change. This is a great way
to both debug your implementation as well as gain intuition about level sampling! See below
for two examples, where we zoom out/in to illustrate how the computed levels change.
• Be careful do not make copies of an entire Miplevel. Make sure you always use a pointer or
a reference to access the miplevel. Copying entire miplevels as arguments is extremely slow!
Complete the given functions.
1RasterizerImp :: rasterize_textured_triangle ()
2Texture :: sample ()
3Texture :: get_level ()
7Your Submissions
The content and quality of your write-up are extremely important, and you should make sure
to at least address all the points listed below. The extra credit portions are intended for students
who want to challenge themselves and explore methods beyond the fundamentals, and are not
worth a large amount of points. In other words, don’t necessarily expect to use the extra credit
points on these projects to make up for lost points elsewhere.
Overview Give a high-level overview of what you implemented in this project. Think about
what you’ve built as a whole. Share your thoughts on what interesting things you’ve learned from
completing the project.
9Task 1 (20 pts + 10 extra) Walk through how you rasterize triangles in your own words.
Explain how your algorithm is no worse than one that checks each sample within the bounding
box of the triangle. Show a png screenshot of basic/test4.svg with the default viewing parameters
and with the pixel inspector centered on an interesting part of the scene. Extra credit: Draw a
triangle “A” over another triangle “B” (both with alpha channel) using z-buffer (10 pts)
Task 2 (20 pts + 10 extra) Walk through your supersampling algorithm and data structures.
Why is supersampling useful? What modifications did you make to the rasterization pipeline in the
process? Explain how you used supersampling to antialias your triangles. Show png screenshots
of basic/test4.svg with the default viewing parameters and sample rates 1, 4, and 16 to compare
them side-by-side. Position the pixel inspector over an area that showcases the effect dramatically;
for example, a very skinny triangle corner. Explain why these results are observed. Extra credit:
1. If you implemented alternative antialiasing methods, describe them and include comparison
pictures demonstrating the difference between your method and grid-based supersampling. (5 pts)
2. When implement supersampling, reduce the memory consumption to the same level w/o super-
sampling. (5 pts)
Task 3 (10 pts) Create an updated version of svg/transf orms/robot.svg with cubeman doing
something more interesting, like waving or running. Feel free to change his colors or proportions
to suit your creativity. Save your svg file as myr obot.svg in your docs/ directory and show a png
screenshot of your rendered drawing in your write-up. Explain what you were trying to do with
cubeman in words.
Task 4 (10 pts) Explain barycentric coordinates in your own words and use an image to aid
you in your explanation. One idea is to use a svg file that plots a single triangle with one red, one
green, and one blue vertex, which should produce a smoothly blended color triangle. Show a png
screenshot of svg/basic/test7.svg with default viewing parameters and sample rate 1. If you make
any additional images with color gradients, include them.
Task 5 (10 pts)
Explain pixel sampling in your own words and describe how you implemented
it to perform texture mapping. Briefly discuss the two different pixel sampling methods, nearest
and bilinear. Check out the svg files in the svg/texmap/ directory. Use the pixel inspector to find
a good example of where bilinear sampling clearly defeats nearest sampling. Show and compare
four png screenshots using nearest sampling at 1 sample per pixel, nearest sampling at 16 samples
per pixel, bilinear sampling at 1 sample per pixel, and bilinear sampling at 16 samples per pixel.
Comment on the relative differences. Discuss when there will be a large difference between the two
methods and why.
10Task 6 (30 pts, 10 extra included)
Explain level sampling in your own words and describe
how you implemented it for texture mapping. You can now adjust your sampling technique by
selecting pixel sampling, level sampling, or the number of samples per pixel. Describe the tradeoffs
between speed, memory usage, and antialiasing power between the three various techniques. Using
a png file you find yourself, show us four versions of the image, using the combinations of L_ZERO
and P _N EAREST , L_ZERO and P _LIN EAR, L_N EAREST and P _N EAREST , as well
as L_N EAREST and P _LIN EAR. To use your own png, make a copy of one of the existing
svg files in svg/texmap/ (or create your own modelled after one of the provided svg files). Then,
near the top of the file, change the texture filename to point to your own png. From there, you can
run ./draw and pass in that svg file to render it and then save a screenshot of your results. Note:
Choose a png that showcases the different sampling effects well. You may also want to zoom in/out,
use the pixel inspector, etc. to demonstrate the differences. Extra credit: If you implemented any
extra filtering methods, describe them and show comparisons between your results with the other
above methods.
