0:00:00.250,0:00:03.337
Once you start looking under the hood, you'll get some sense of the lay of the

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land with matrices and how they relate to transforms. Here's a map of the sort

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of things you'll find. The upper left area of the matrix is where rotations and

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scales show up. If a transform changes only this area of the matrix, it's called

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a linear transformation. I'm not going to spend time on the formal definition of

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this term. The additional course materials include resources for more on the

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underlying math. The definition is fairly basic stuff about how addition and

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multiplication are preserved. But doesn't have much effect on how we actually do

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computer graphics. The upper right is where the translations accumulate. These

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translation values will get effected by multiplication with other matrices of

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course. Translations only effect points since vectors have zero for their fourth

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coordinate. 3JS provides a function called decompose to extract the translation,

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rotation and scale factors from a matrix. The translation and scale factors come

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back as vectors, as you might expect. The rotation comes back as a quaternion.

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Something we'll talk about when we get to animation. The short version is that a

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quaternion is a compact way to store the axis and angle of rotation for a

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rotation matrix. One useful property quarternions have is that you can easily

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interpolate between them, which is useful for interpolating between two

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different orientation. Notice that the bottom row is always 0, 0, 0 1. The

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transforms we covered here are called affine transforms. Parallel lines stay

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parallel when an affine transform is applied. In modeling you'll essentially

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always use affine transforms. So we never change this last row. Since GPUs are

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tuned to use four by four matrices Most of us just use four by fours everywhere

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for simplicites sake. When we discuss perspective cameras, we'll set the values

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in this last row. We'll then be using a projective transform. With affine

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transforms, when a points coordinates are multipied by the matrix. The fourth

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coordinate starts out as one and ends up as one. This last row in a projection

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matrix modifies that fourth coordinate to be something other than one. What that

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means is something we'll leave til a later lesson.