Animation Compression Library
Animation compression is a fundamental aspect of modern video game engines. Not only is it important to keep the memory footprint down but it is also critical to keep the animation clip sampling performance fast.
The more memory an animation clip consumes, the slower it will be to sample it and extract a character pose at runtime. For these reasons, any game that attempts to push the boundaries of what the hardware can achieve will at some point need to implement some form of animation compression.
While some degree of compression can easily be achieved with simple tricks, achieving high compression ratios, fast decompression, while simultaneously not compromising the accuracy of the resulting compressed animation requires a great deal of care.
This library has four primary goals:
Algorithms are optimized with a focus on (in this particular order):
Decompression speed will not be sacrificed for a smaller memory footprint nor will accuracy be compromised under any circumstances.
Much thought was put into designing the library for it to be as flexible and powerful as possible. To this end, the following decisions were made:
The above supported platform list is only what is tested every release but if it compiles, it should run just fine.
The Unreal Engine is supported through a plugin found here.
This library is 100% headers as such you just need to include them in your own project to start using it. However, if you wish to run the unit tests, regression tests, to contribute to ACL or use it for research, head on over to the getting started section in order to setup your environment and make sure to check out the contributing guidelines.
If you would like to integrate ACL into your own game engine, follow the integration instructions here.
You can install nfrechette-acl
with Conan.
You donβt need anything else to get started: everything is self contained.
See here for details.
This project uses the MIT license.
Copyright Β© 2017 Nicholas Frechette & Animation Compression Library contributors
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
Thanks goes to these wonderful people (emoji key):
This project follows the all-contributors specification. Contributions of any kind welcome!