Skip to content

Computer Graphics, Fall Semester 2019, Practical Assignment 3

Notifications You must be signed in to change notification settings

Jacobs-University/eyden-tracer-03

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

36 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Practical Assignment 3

Dealine: 28.10.2021

Please put your name here:
Name: .......

Problem 1

Rendering complex geometry (Points 5)

Until now we have only hardcoded our scene geometry in main.cpp. This is of course not practical. In the new framework, a class CSolid is added. This class may contain complex geometry formed by multiple primitives. Such geometry may be saved / read from an .obj file. For this problem we will read torus knot.obj file and rended this object, which consists of 12 960 triangles. To make the method work proceed as follows:

  1. Fork the current repository
  2. Modify the README.md file in your fork and put your name above.
  3. Have a look at the file torus knot.obj and at the class CSolid. Study how triangles are stored in the obj-format and in the class. The v ’s indicate a single 3d-vertex position, and the f ’s (faces) are indecies to 3 vertex numbers a triangle consits of (please note that the face indecies are starting with 1 and not 0).
  4. Implement function CScene::add(const CSolid& solid) which adds a solid to the scene.
  5. Make sure that you work with Release and not Debug and disable BSP support in CMake (if it was enabled). Render the scene and write the time needed for 1 frame below:
    T0: .......

Note: Rendering may take several minutes.

If your implementation works as expected you should see an image of a torus knot like this:

Torus Knot

Hint: The obj file-format can be dumped out from various 3d-modelers. Nevertheless, the output might differ from modeler to modeler and there are also other tokens like vn for vertex normals or vt for texture coordinates. Check obj file format for a full description.

Problem 2

Multi-threading (Points 15)

As we have learned from Problem 1, the increased number of the primitives in scene makes rendering with raytracing inefficient and thus useless. So, the rest of the current assignment will be dedicated to acceleration techniques. One of the most naive ideas to accelerate raytracing would be to increase the CPU power. In order to use not one but all cores of CPU proceed as follows:

  1. Study the OpenCV function for parallel data processing parallel_for_: How to use the OpenCV parallel_for_ to parallelize your code
  2. In main.cpp file rewrite the main rendering loop (lines 53 - 57), by paralellizing the loop for (int y = 0; y < img.rows; y++) with help of parallel_for_ function and enclosing the inner body into a lambda-expression. You do not need to parallelize the inner loop for (int x = 0; x < img.cols; x++).
  3. Render the scene and write the time needed for 1 frame T1 and speedup = T0 / T1 below:
    T1: .......
    Speedup: .......

Problem 3

Implementation of a kd-tree acceleration structure (Points 30)

So far, your own ray tracer implementation has used no acceleration structure for reducing the number of ray / primitive intersections. This was simple to implement and worked relatively good. Unfortunately, this, of course, is not practical for larger scenes as you have noticed in the last problems with the torus knot. As such, you need a data structure to speed up the process of finding the first hit of a ray with the primitives. In recent years the kd-tree proved to be a useful acceleration data structure for minimizing ray-intersection tests. To implement your kd-tree proceed as follows:

  1. Study n new class CBoundingBox is now in the framwork which contains two Vec3f’s for the m_minPoint, m_maxPoint - fields of the bounding box. Furthermore the class has 2 methods void CBoundingBox::extend(const Vec3f& p) and void extend(const CBoundingBox& box). Enable BSP support in CMake and implement the following functionality:
    1. If point p is not inside a bounding box b, b.bxtend(p) should extend the bounding box until it also includes p.
    2. If box box is not fully inside a bounding box b, b.bxtend(box) should extend the bounding box until it also includes box.
      Tip: The box is initialized with an ’empty box’ (m_minPoint = +infinity, m_maxPoint = −infinity).
      Hint: You may make use of functons Min3f and Max3f defined in the BoundingBox.cpp file.
  2. The method virtual CBoundingBox getBoundingBox(void) const = 0 has to be implemented in every class derived from IPrim.
  3. Most acceleration structures require to clip the ray with the bounding box of the scene, as the origin might otherwise be outside the scene bounds. For clipping a ray with the bounding box of a scene, you can best use the slabs algorithm and implement it in void CBoundingBox::clip(const Ray& ray, double& t0, double& t1).
  4. You will need a method to decide whether a primitive is contained in a given bounding box or not. For this purpose the method bool CBoundingBox::overlaps(const CBoundingBox& box) const exists. Implement theis method. For simplicity, just check the primitives bounding box for overlap with the box.
  5. Implement the method CBoundingBox calcBoundingBox(const std::vector<ptr_prim_t>& vpPrims) in BSPTree.h file, which should calculate the bounding box of the scene, containing all the primitives given by vpPrims.
    Hint: Use the void extend(const CBoundingBox& box) function.
    If everything so far was implemented correctly, the Scene bounds will be: [-6, 0, -5.6] [4.45, 8, 5.6] (approximately)
  6. Implement the method std::pair<CBoundingBox, CBoundingBox> CBoundingBox::split(int dim, float val) const which splits curent bounding box into two pieces. The split should be done with a hyper-plane orthogonal to the axis defined by argument dim and in the positon defined by argument val.
  7. Implement the method std::shared_ptr<CBSPNode> build(const CBoundingBox& box, const std::vector<ptr_prim_t>& vpPrims, size_t depth) of the class CBSPTree. Use the ideas presented at the lecture. As soon as you have reached a maximum depth (e.g. 20), or you have less then a minimum number of primitives (e.g. 3 or 4), stop subdividing and generate a leaf node. Otherweise, split your bounding box in the middle (in the maximum dimension), sort your current primitives into two vector left and right, and recursively call BuildTree with the respective bounding boxes and vector for left and right. Start subdivision with a list of all primitives, the total scene bounds, and an initial recursion depth of 0.
  8. For traversal, use a simple, recursive algorithm, described in the lectures. Please implement this algorithm in methods bool CBSPTree::intersect(Ray& ray) and bool CBSPNode::intersect(Ray& ray, double t0, double t1) For more information please read the chapter 7.2 in the thesis of Dr. Ingo Wald.
  9. Implement the method std::shared_ptr<CBSPNode> build(const CBoundingBox& box, const std::vector<ptr_prim_t>& vpPrims, size_t depth) of the class CBSPTree. Use the ideas presented at the lecture. As soon as you have reached a maximum depth (e.g. 20), or you have less then a minimum number of primitives (e.g. 3 or 4), stop subdividing and generate a leaf node. Otherweise, split your bounding box in the middle (in the maximum dimension), sort your current primitives into two vector left and right, and recursively call BuildTree with the respective bounding boxes and vector for left and right. Start subdivision with a list of all primitives, the total scene bounds, and an initial recursion depth of 0.
  10. Render the scene and write the time needed for 1 frame T2 and speedup = T0 / T2 below:
    T2: .......
    Speedup: .......

A the solution for this problem can be found in OpenRT library: www.openrt.org However it is highly recommended to solve this problem using lecture slides only and resorting to the solution only as a last resort.

Instead of optimizing too much, rather concentrate on a stable, bug-free implementation.

Problem 4

Optimization of the KD-Tree build algorithm (Points 50)

The performace of ray traversal in a kd-tree highly depends on the structure of a particular tree. For the same scene it is possible to build a kd-tree in multiple ways. For this problem we will research the tree building algorithm and try to ptimize it. The core idea of the kd-tree building algorithm is splitting a current bounding box into 2 leafs. For that purpose on the lectures we have considered splitting dimension splitDim to be the maximum dimension of the bounding box and splitting value splitVal to be the center of of the box in that dimension.

  1. Elaborate and implement your idea in ptr_bspnode_t CBSPTree::build(const CBoundingBox& box, const std::vector<ptr_prim_t>& vpPrims, size_t depth) for better choice of the splitVal parameter. For example, define splitVal in such a way, that the number of primitives in the current bounding box will be split by half. To check your implememntation you may chech the length of the left and right vectors with primitives after the split.
  2. Elaborate and implement your idea in ptr_bspnode_t CBSPTree::build(const CBoundingBox& box, const std::vector<ptr_prim_t>& vpPrims, size_t depth) for better choice of the splitDim parameter. For example, define splitVal as a function of max dimension and depth of the recursion.
  3. Experiment with your ideas. Chose the one, which gives the fastest result and render the scene and write the time needed for 1 frame T3 and speedup = T0 / T3 below:
    T3: .......
    Speedup: .......

Submission

Please submit the assignment by making a pull request. Important : Please make sure that

  • No extra files are submitted (except those, which were mentioned in the assignment)
  • The changes were made only in those files where you were asked to write your code
  • The Continiouse Integration system (appVeyor) can build the submitted code
  • The rendered images are also submitted in the folder "renders"

About

Computer Graphics, Fall Semester 2019, Practical Assignment 3

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages