AR CAT
Creating 3D Assets Through
Scanning And Capture
Today, creating 3D assets doesn’t have to start from scratch. Thanks to modern technology, real-world objects can be captured and turned into detailed digital models using devices like LiDAR scanners, DSLR cameras, or even a smartphone. The process begins with capturing the object or environment. LiDAR sensors use laser light to measure depth and shape with high precision, ideal for scanning large or complex surfaces. DSLR cameras offer high-resolution images perfect for photogrammetry, while smartphones provide a more accessible way to capture 3D data with surprising quality.
Once captured, the data is processed using advanced technologies. Photogrammetry stitches overlapping images to recreate detailed 3D models. 3D Gaussian Splatting (3DGS) represents scenes with small, efficient point clouds, allowing for quick, real-time rendering. Neural Radiance Fields (NeRF) take a different approach, using AI to generate realistic, volumetric 3D scenes based on how light behaves across images. After processing, the 3D models are refined using tools like Blender or Autodesk Maya. Here, the models are cleaned, optimized, textured, and prepared for their final use.
Finished assets can be imported into game engines like Unreal Engine or Unity, integrated into web experiences through platforms like Three.js, or shared on 3D marketplaces. This streamlined approach makes high-quality 3D content more accessible than ever, powering everything from games and films to interactive websites and virtual reality.
Photogrammetry is the art and science of creating accurate 3D models from a series of photographs. By capturing multiple overlapping images of an object or environment from different angles, photogrammetry software uses algorithms to analyze visual data, detect common points between images, and calculate depth and spatial relationships. This process, known as structure-from-motion (SfM) and multi-view stereo (MVS), reconstructs detailed shapes, textures, and dimensions from simple 2D photos.
The quality of the final model largely depends on the clarity, coverage, and consistency of the source images. With advances in camera technology and powerful photogrammetry software, this method has become more accessible — allowing anyone with a DSLR or even a smartphone to create professional-grade 3D assets. Whether capturing a small product or an entire landscape, photogrammetry offers a cost-effective and highly detailed solution for bringing real-world objects into digital environments.
From simple photo studios to multi-phone camera rigs, ARCAT PLT provides efficient, high-quality capture setups tailored to customer needs — balancing performance with practicality.
Artificial intelligence is reshaping how we capture and recreate 3D worlds. Neural Radiance Fields (NeRF) is an AI-based technology that learns how light interacts with surfaces from a series of 2D images. Instead of building a traditional 3D mesh, NeRF creates a volumetric representation of the scene, allowing highly realistic views from any angle. It excels at capturing fine details like soft edges, transparency, and complex lighting that traditional methods struggle to reproduce.
3D Gaussian Splatting (3DGS) takes a different, AI-driven approach. Rather than constructing solid models, 3DGS represents scenes with tiny, soft "splats" — points with position, color, and size — to form a visually complete 3D object. This method is extremely fast and lightweight, making it ideal for real-time applications like interactive web experiences or VR. Both NeRF and 3DGS are pushing the boundaries of 3D content creation, offering new ways to capture reality with speed, efficiency, and stunning visual quality.
Leveraging our in-house hardware and trusted partner technologies, ARCAT PLT helps bring your 3D asset vision to life — tailored to fit your production requirements and platform goals.
