---
title: UE5 3DGaussians 插件笔记
date: 2023-12-22 11:44:33
excerpt: 
tags: 
rating: ⭐
---

# c++
插件的c++部分主要实现了
- FThreeDGaussians——可以理解为一个场景或者根节点
	- FThreeDGaussiansTree——类似BVH的空间切分树
	- FThreeDGaussiansData——具体数据
- ply点云文件导入,流程如下
	- FThreeDGaussiansImporterModule::PluginButtonClicked()
	- LoadPly(),载入`TArray<FThreeDGaussian>`数据。
	- 进行排序
		- 初始化一个`TArray<FThreeDGaussianSortPair> unsorted`并且进行排序。
		- 取得各种排序用参数DO_SPLIT_BY_3D_MORTON_ORDER、DO_SPLIT_BY_DISTANCE、MAX_TEXTURE_WIDHT、MAX_NUM_PARTICLES
		- 采用莫顿码分割法、距离排序法。
			- 莫顿码分割法:使用莫顿码进行排序,之后进行空间分割,构建一个三维加速结构。当当前区域点云数量小于MAX_NUM_PARTICLES后调用CreateDatum()。
			- 距离排序法:根据Position上三个分量中最大绝对值进行排序,之后调用CreateDatum()。
	- CreateDatum()
		- Sort3dMortonOrder()排序。
		- CreateExr()创建Exr Texture文件。
		- 将上一步创建的文件导入UE。
	- CreateActorBpSubclass(),创建3DGaussians蓝图Actor,并且查找SetData函数并且将数据塞入。

## FThreeDGaussians代码
```c++
struct FThreeDGaussiansData
{
	GENERATED_BODY()
public:
	FThreeDGaussiansData() {}
	FThreeDGaussiansData(const TArray<UTexture2D*>& textures, const FVector3f& in_minPos, const FVector3f& in_maxPos)
	{
		minPos = in_minPos;
		maxPos = in_maxPos;
		textureWidth = textures[0]->GetSizeX();
		position = textures[0];
		rotation = textures[1];
		scaleAndOpacity = textures[2];

		for (int i = 3; i < textures.Num(); i++)
		{
			sh.Add(textures[i]);
		}
	}

	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians") FVector3f minPos = FVector3f::Zero();
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians") FVector3f maxPos = FVector3f::Zero();
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians") int32 textureWidth = -1;
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians") UTexture2D* position;
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians") UTexture2D* rotation;
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians") UTexture2D* scaleAndOpacity;
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians") TArray<UTexture2D*> sh;
};

/** 类似BVH的控件数据结构 */
USTRUCT(BlueprintType)
struct FThreeDGaussiansTree
{
	GENERATED_BODY()
public:
	FThreeDGaussiansTree() {}

	// Axis for split (x=0, y=1, z=2)
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians")	int32 splitAxis = -1;
	// max value of the position of gaussian in child0 or leaf0 in "splitAxis" axis
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians")	float splitValue = 0.0f;

	// index of child tree node (Index of TArray<FThreeDGaussiansTree> tree)
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians")	int32 childIndex0 = -1;
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians")	int32 childIndex1 = -1;

	// index of child data node (Index of TArray<FThreeDGaussiansData> data)
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians")	int32 leafIndex0 = -1;
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians")	int32 leafIndex1 = -1;
};

/* 作为3D高斯数据的载荷 */
USTRUCT(BlueprintType)
struct FThreeDGaussians
{
	GENERATED_BODY()
public:
	FThreeDGaussians() {}

	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians") TArray<FThreeDGaussiansData> data;
	UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "3D Gaussians") TArray<FThreeDGaussiansTree> tree;
};
```

# BP_3D_Gaussians_Base
- BeginPlay:判断三维加速结构是否还子节点,如果有则开启Tick进行排序。
- Tick:根据摄像机位置对三维加速结构进行排序。
- ConstructionScript:
	1. 添加Niagara粒子组件,一个FThreeDGaussiansData生成一个粒子组件。
	2. 设置Niagara资产:NS_3D_Gaussians_sh0_mesh(勾选mesh选项)、NS_3D_Gaussians_sh0(SH角度)、NS_3D_Gaussians_sh1、NS_3D_Gaussians_sh2、NS_3D_Gaussians_sh3
	3. 设置粒子材质属性:
		1. AlbedoTint
		2. 剔除设置:CropEnabled、CropTranslation、CropRotation、CropExtent
		3. 数据贴图(FThreeDGaussiansData):texture_width、texture_position、texture_rotation、texture_scaleAndOpacity。
		4. SH数据贴图(FThreeDGaussiansData):根据角度设置Niagara里texture_sh_X的贴图。
		5. 社会中剔除空间 CropTranslations、CropRotators、CropExtents、KillTranslations、KillRotators、KillExtents。


# 实现思路
## 4D高斯
1. 实现一个Niagara Module实现对Texture2DArray贴图采样。
2. ~~使用Niagara Cache~~。
3. 考虑 TextureStream机制以此节约显存。

## 使用RVT实现3D高斯 LOD思路
AI数据侧:
1. 确定点云数据是否可以划分成四叉树的数据结构,也就是将一堆点云按照一个**距离阈值** 进行分割,最终形成一个四叉树。
	1. 确定是否可以生成金字塔结构贴图(直接写入到Mipmap结构里),或者生成多张基于2的幕长度贴图。

UE侧:
目前已经测试过SVT可以放入到Niagara Texture Sampler中。同时也可以将SVT放到Texture2DArray中。
1. 将3D高斯各种贴图制作成SVT之后塞入Texture2DArray,在Niagara中采样。
2. 在Niagara中根据Niagara 粒子ID对SVT进行采样。