3D Gaussian Splatting vs. Photogrammetry: What’s the Difference and Why It Matters

Gaussian Splatting is quickly emerging as one of the most exciting breakthroughs in the world of 3D scanning and real-time graphics. For industries working in VR, AR, digital twins, and immersive storytelling, it promises faster workflows, more lifelike visuals, and real-time rendering performance unlike anything photogrammetry can achieve on its own.

But what exactly is Gaussian Splatting? How does it compare to traditional photogrammetry?

And when should you use one technique over the other?

In this comprehensive guide, we break down what Gaussian Splatting is, how it works, and how it stacks up against photogrammetry in terms of workflow, output quality, cost, and best-use scenarios.

Exploring the contrast between 3D Gaussian Scanning and Photogrammetry: A detailed look at their differences, pros and cons, techniques, costs, and applications, featuring a setup with a camera, drone, and classical busts.

What Is Gaussian Splatting?

Gaussian Splatting is a novel technique for rendering 3D scenes using millions of overlapping volumetric particles, or "Gaussians", each carrying color, transparency, position, and size data. These Gaussians replace the need for traditional polygon meshes by creating a soft, continuous representation of objects and environments directly from captured images.

This method evolved from research into Neural Radiance Fields (NeRFs) but improves drastically on rendering speed and visual quality, making it practical for real-time applications like VR, AR, and interactive 3D content.

Key Characteristics of Gaussian Splatting

• Uses point-based rendering, not mesh geometry.

• Delivers high-fidelity, cinematic-quality visuals.

• Can run in real-time on modern GPUs.

• Ideal for scanning environments, objects, and full scenes.
  

How Gaussian Splatting Works

1. A camera (or set of cameras) captures a series of overlapping images.

2. These images are aligned using camera tracking data or structure-from-motion techniques.

3. A neural network processes the data to place millions of 3D Gaussians throughout the scene.

4. Each Gaussian contains position, color, and light scattering properties.

5. The scene is rendered in real time using a GPU-accelerated renderer.
   

The end result is a scene that appears volumetric and highly photoreal, without the need for polygon modeling or traditional texture mapping.

What Is Photogrammetry?

Photogrammetry is a proven method that reconstructs 3D geometry by analyzing multiple 2D photographs taken from different angles. It generates a dense point cloud, which is then converted into a 3D mesh with a photo texture overlaid.

Photogrammetry is widely used in architecture, archaeology, game development, and product visualization due to its ability to produce precise, editable 3D models.

Key Steps in Photogrammetry

1. Capture hundreds of high-resolution images.

2. Stitch and align images using photogrammetry software.

3. Generate a dense point cloud.

4. Convert point cloud into a mesh.

5. Apply texture mapping for realism.

6. Export to 3D file formats for further use in engines like Unity or Unreal.

Gaussian Splatting vs Photogrammetry: What’s the Difference?

While both techniques convert real-world imagery into 3D digital form, the approach, output format, and applications are fundamentally different.

Output Comparison

Feature	Gaussian Splatting	Photogrammetry
Format	Volumetric Gaussian particles	Polygon mesh with textures
Editability	Limited (non-mesh based)	Fully editable mesh
File Size	Smaller and GPU-optimized	Larger with detailed geometry
Output Type	Real-time renderer	Exportable 3D asset
Compatibility	Optimized for real-time rendering (VR, AR)	CAD, games, 3D printing, VFX

Workflow and Performance

Feature	Gaussian Splatting	Photogrammetry
Image Input Required	20–50 images	100–500+ images
Real-Time Ready	Yes	Not natively
Software	Custom or open-source AI tools	Agisoft, RealityCapture, Meshroom
Hardware Requirements	High-performance GPU	DSLR or mirrorless cameras, CPU/GPU

Visual Quality

• Gaussian Splatting delivers smooth lighting transitions, cinematic depth, and realistic parallax.

• Photogrammetry provides surface precision and detail, useful for engineering and digital twins where exact geometry matters.

Advantages of Gaussian Splatting

1. Real-Time PerformanceGaussian Splatting can be rendered in real time, making it perfect for VR, XR, and web-based interactive environments.

2. Cinematic VisualsLighting, shadows, and materials appear soft and natural, similar to film-like rendering or volumetric photography.

3. Minimal Input, Maximum OutputIt requires far fewer images to build a complete 3D representation compared to traditional photogrammetry.

4. No Mesh CleanupBecause the output is point-based, there’s no need for UV unwrapping, decimation, or manual retopology.

5. AI-Native and ScalableBuilt for the AI generation of tools, it fits into automated pipelines and future neural graphics workflows.

Limitations of Gaussian Splatting

• Difficult to Edit: You cannot manipulate or animate individual components like you would in a mesh-based model.

• Incompatible With CAD or Print: Outputs are not suitable for 3D printing or engineering analysis.

• Experimental Ecosystem: Still a cutting-edge method with tools primarily in research or developer stages.

• Requires Technical Expertise: Most pipelines require Python, command-line tools, and ML model management.

Cost Breakdown

Factor	Gaussian Splatting	Photogrammetry
Camera Equipment	Low (action cam or phone)	Medium to High (DSLR + lighting)
Software	Free (open-source)	$0–$1500 depending on license
Processing Time	Fast	Slow (image cleanup, mesh generation)
Editing Flexibility	Low	High
Real-Time Compatibility	Native	Not native (needs optimization)

Best Use Cases for Gaussian Splatting

• Virtual Reality Scenes: Realistic, responsive worlds with low latency and lifelike depth.

• AR/VR Training Simulations: Lightweight assets for headset deployment with fast load times.

• Exhibitions and Museums: Real-time, cinematic captures of environments or installations.

• Digital Twins for Live Monitoring: Interactive spatial scans that run in real time for remote collaboration.

• Virtual Showrooms: Showcasing environments with rich visual depth and intuitive interaction.

When to Choose Photogrammetry Instead

• Precision modeling for CAD or 3D printing

• Objects with clear edges, labels, or fine structure

• Scenes needing export to traditional 3D engines

• Animation pipelines requiring character rigging

• Static architectural visualization or reverse engineering

How Canopy Creative Uses Gaussian Splatting

At Canopy Creative, we integrate Gaussian Splatting into our immersive design workflows for clients in education, entertainment, and commercial sectors. We use it to create ultra-realistic environments and interactive scenes that load instantly on VR headsets, WebXR browsers, or XR displays.

When projects require traditional deliverables, like printable 3D assets or animated characters, we blend in photogrammetry or LiDAR scanning.

Our hybrid approach ensures you're using the right tool for the right task, without compromising on performance or visual fidelity.

Gaussian Splatting Is the Future of Real-Time 3D Capture

As real-time 3D continues to evolve, Gaussian Splatting offers a glimpse into the future of how environments are digitized, rendered, and shared. While photogrammetry remains an essential tool for precision modeling, Gaussian Splatting delivers unmatched performance and visual realism for immersive experiences.

If you’re developing a VR training app, building a virtual showroom, or launching an interactive brand campaign, Gaussian Splatting is one of the most efficient, scalable, and visually impressive technologies available today.

Want to explore how Gaussian Splatting can power your next project?

Visit www.canopycreative.design to connect with our team.