A C++ library for decomposing 3D meshes into approximate convex parts for efficient collision detection in games and simulations.
V-HACD is a C++ library that performs approximate convex decomposition of 3D meshes, breaking down complex concave shapes into simpler, near-convex parts. It solves the problem of inefficient collision detection in real-time applications like video games, where using exact convex decompositions is computationally prohibitive. By allowing tunable concavity thresholds and hull counts, it provides a practical balance between accuracy and performance.
Game engine developers, physics simulation engineers, and 3D software tool creators who need efficient collision detection for concave objects in real-time interactive applications.
Developers choose V-HACD for its proven reliability, tunable performance, and ease of integration as a header-only library. It offers a pragmatic alternative to exact decomposition methods, enabling real-time collision detection without the computational overhead of minimal convex partitioning.
Automatically exported from code.google.com/p/v-hacd
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Version 4.0 is implemented as a single header file, eliminating complex linking and simplifying drop-in usage for C++ projects.
The rewrite in version 4.0 results in faster, more robust decomposition with fewer bugs compared to older versions, as noted in the README.
Developers can control voxel resolution, decomposition depth, and hull count to balance accuracy and performance, with examples provided for fine-tuning.
Widely adopted in game development and physics simulations, it offers a pragmatic approach to convex decomposition for real-time applications.
The project is archived and no longer receives updates or bug fixes, with the README explicitly recommending CoACD for new development.
Unlike modern tools, it requires users to predefine the number of convex hulls, which can lead to guesswork and suboptimal results if not carefully tuned.
Achieving accurate decompositions with low error thresholds and high voxel resolutions can result in very long processing times, as highlighted in the tuning examples.