Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fix Extra Cull Margin triggers worst LOD #79191

Closed
wants to merge 1 commit into from

Conversation

fire
Copy link
Member

@fire fire commented Jul 8, 2023

DRAFT PR.

It introduces a new condition that checks if the transformed AABB (Axis-Aligned Bounding Box) contains the camera's origin point. If it does, it calculates a scale factor based on the distance between the camera and the center of the AABB, and applies this factor to adjust the distance value.

Fixes: #67890

It introduces a new condition that checks if the transformed AABB (Axis-Aligned Bounding Box) contains the camera's origin point. If it does, it calculates a scale factor based on the distance between the camera and the center of the AABB, and applies this factor to adjust the distance value.
@lyuma
Copy link
Contributor

lyuma commented Jul 8, 2023

I'm confused...
If (inst->transformed_aabb.has_point(p_render_data->scene_data->cam_transform.origin)), shouldn't it always use the best quality LOD (distance = 0)?

What exact case is this code addressing and how does it do it?

@YuriSizov
Copy link
Contributor

Now that #79590 is merged, we should reevaluate if this is still something desired or not.

@fire
Copy link
Member Author

fire commented Jul 24, 2023

Will revisit in the future. Thanks!

@fire fire closed this Jul 24, 2023
@fire fire deleted the worst-lod-distances branch October 3, 2023 17:52
@AThousandShips AThousandShips removed this from the 4.x milestone Nov 1, 2023
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

Successfully merging this pull request may close these issues.

Extra Cull Margin triggers worst LOD
5 participants