I am using animation channels which are arrays containing one value per frame, I came up with the idea of not storing the array if all the values are the same, so the value is stored only once, I call this, obviously, a constant channel.
From there I thought I could do something about other channels that change too little, for example for some sort of trigger channel, where values are mostly zeros with ones here and there to signal a sound or that a footprints, so I added Run Length Encoding channels.
So far so good but! once I came to store joint transformations I noticed that when I store full model space transforms, the children joints change as the parent changes because the transform 'includes' the parent's transform, so transformation vectors do not compress well this way.
However, if I store the joint transforms in 'parent space', if a joint never moves or rotates or scales, its values never change and thus, very good compression ratios can be achieved.
Now, the problem is that if I store the transforms in parent space, I still need to calculate the transforms in model space at run time, and that may involve several matrix multiplications that are avoided if the transforms are precomputed as is in the first case.
So my question is... what should I do? should I go for (perceived) speed or size? is this even a valid concern? perhaps the overhead is negligible, or maybe a smaller memory footprint compensates for the computation cost, I don't know.
Ideas? Discuss!
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