Overview

Build photoreal game levels from real scenes and ship them in Unity and Unreal with workflows that hold up under production pressure. Turning scans into playable content is hard. Camera poses drift, floaters creep into windows, and frame time slips when scenes scale. Teams need a reliable path from capture to engine that keeps quality high and performance predictable. This book gives you a practical pipeline. You will capture consistently, train fast with Gaussian splats and NeRF variants, export engine ready assets, and integrate them cleanly in URP, HDRP, and UE5 with Lumen, VR, and WebGPU delivery covered. Choose the right representation and SH degree for speed, memory, and fidelity Run stable capture, pose recovery, calibration, and undistortion for clean datasets Train with Splatfacto and Splatfacto W, add depth regularization, and avoid floaters Use gsplat and accelerated rasterizers, know when they help and why Set visibility, depth handling, anti aliasing, and mip strategies that stay stable Measure quality with PSNR SSIM LPIPS and camera path benchmarks that catch regressions Convert PLY to compact SPZ with SH preservation, orientation, and tiling for streaming Stand up batch exporters and converters that do not break on large jobs Stream city scale scenes with tile grids, CDN friendly manifests, and clear budgets Integrate in Unity URP and HDRP, master transparency sorting, queues, and depth prepass Integrate in UE5 with translucent materials, Lumen lighting, and stable sorting Build mesh proxies with SuGaR for collisions, nav, and occlusion wherever needed Mix splats with Nanite meshes and classic assets without visual seams Plan VR for Quest with Vulkan first, stereo correctness, foveation, and near plane control Deliver on web with WebGPU and web viewers, manage file size and bandwidth Profile bottlenecks, thread wisely, and scale out with nDisplay and multi machine setups Apply pruning, scale regularization, and culling policies that reduce shimmer Automate metric gates, screenshots, and video for repeatable regression checks Follow release checklists, change guards, and production sign off steps that prevent surprises Work through playbook case studies, from a one day indoor room to a streamed city block Extras included, grounded in the manuscript, to speed real work: production playbooks, a release checklist and change guards, camera path benchmarks, and QA procedures with regression tracks. This is a code heavy guide. Working snippets in Python, Shell, JSON, YAML, C++, and GLSL demonstrate training drivers, exporters, SH evaluation, rasterization loops, streaming managers, and profiling harnesses so you can plug them into real projects. Get the workflow your team can trust, purchase your copy today.

Full Product Details

9798273427440

Table of Contents

Reviews

Author Information

Tab Content 6

Countries Available