Assignment 1

Name: Ayush Pandey Andrew ID: ayushp

All the outputs are saved in the folder ouput with the the name as argument_name.gif

1. Practicing with Cameras

1.1. 360-degree Renders (5 points)

On your webpage, you should include a gif that shows the cow mesh from many continously changing viewpoints.

python main.py --question_number q1_1 

1.2 Re-creating the Dolly Zoom (10 points)

On your webpage, include a gif with your dolly zoom effect.

python main.py --question_number q1_2

2. Practicing with Meshes

2.1 Constructing a Tetrahedron (5 points)

On your webpage, show a 360-degree gif animation of your tetrahedron. Also, list how many vertices and (triangle) faces your mesh should have.

python main.py --question_number q2_1

Number of Faces = 4, Number of Vertices = 4

2.2 Constructing a Cube (5 points)

On your webpage, show a 360-degree gif animation of your cube. Also, list how many vertices and (triangle) faces your mesh should have.

python main.py --question_number q2_2

Number of Faces = 12, Number of Vertices = 8

3. Re-texturing a mesh (10 points)

In your submission, describe your choice of color1 and color2, and include a gif of the rendered mesh.

python main.py --question_number q3

Color choices:

color1 = torch.tensor([1, 1, 0])
color2 = torch.tensor([0, 1, 1])

4. Camera Transformations (20 points)

In your report, describe in words what R_relative and T_relative should be doing and include the rendering produced by your choice of R_relative and T_relative.

4.1

python main.py --question_number q4_1

The cow is rotated by 90 degrees with y axis as the axis of rotation. There is no translation.

Camera parameters:

R = pytorch3d.transforms.euler_angles_to_matrix(
                                    torch.tensor([0, np.pi/2, 0]), "XYZ")
    
T = torch.tensor([[0, 0, 3]])

4.2

python main.py --question_number q4_2

The cow is rotated by -90 degrees with z axis as the axis of rotation. There is no translation.

Camera Parameters

R = pytorch3d.transforms.euler_angles_to_matrix(
                                    torch.tensor([0, 0, -np.pi/2]), "XYZ")
    
T = torch.tensor([[0, 0, 3]])

4.3

python main.py --question_number q4_3

There is no rotation. We move away in from the cow by 2 units (in the z direction)

Camera Parameters

R = torch.eye(3)
T = torch.tensor([[0, 0, 5]])

4.4

python main.py --question_number q4_4

There is no rotation. We translate in x direction by -0.5 and y direction by 0.5

Camera Parameters

R = torch.eye(3)
T = torch.tensor([[0.5, -0.5, 3]])

5. Rendering Generic 3D Representations

5.1 Rendering Point Clouds from RGB-D Images (10 points)

In your submission, include a gif of each of these point clouds side-by-side.

python main.py --question_number q5_1

5.2 Parametric Functions (10 points)

In your writeup, include a 360-degree gif of your torus point cloud, and make sure the hole is visible. You may choose to texture your point cloud however you wish.

python main.py --question_number q5_2 --num_points 100

Number of points = 100

Number of points = 1000

5.3 Implicit Surfaces (15 points)

In your writeup, include a 360-degree gif of your torus mesh, and make sure the hole is visible. In addition, discuss some of the tradeoffs between rendering as a mesh vs a point cloud. Things to consider might include rendering speed, rendering quality, ease of use, memory usage, etc.

python main.py --question_number q5_3

Trade-Offs:

• With the same number of vertices in point clouds and mesh, it would be faster to render a point cloud as compared to mesh
• Mesh stores connectivity information of the topology that its representing whereas point cloud does not. To render at the same quality as mesh we will have to sample a lot of points for the point cloud.
• Mesh uses more memory as compared to point clouds as apart from vertices its also saving the faces information
• Both are equally easy to use.

6. Do Something Fun (10 points)

python main.py --question_number q6

7. (Extra Credit) 7. Sampling Points on Meshes (10 points)

For this part, write a function that takes a triangle mesh and the number of samples and outputs a point cloud. Then, using the cow mesh, randomly sample 10, 100, 1000, and 10000 points. Render each pointcloud and the original cow mesh side-by-side, and include the gif in your writeup.

python main.py --question_number q_7