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Convert figure images to markdown

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James Gregory 2013-12-31 07:56:10 +11:00
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@ -28,9 +28,8 @@ equally. What it all works out to is that the value of the dot product
of any vector with a unit vector is the length of the first vector
projected onto the unit vector, as shown in Figure 61.6.
![](images/61-06.jpg)\
**Figure 61.6**  *How the dot product with a unit vector performs a
projection.*
![**Figure 61.6**  *How the dot product with a unit vector performs a
projection.*](images/61-06.jpg)
This unlocks all sorts of neat stuff. Want to know the distance from a
point to a plane? Just dot the vector from the point **P** to the plane
@ -94,9 +93,8 @@ on. So when two 3-D experts, John Carmack and Billy Zelsnack, mentioned
that they think of rotation differently, in a way that seemed more
intuitive to me, I thought it was worth passing on.
![](images/61-07.jpg)\
**Figure 61.7**  *Using the dot product to get the distance from a
point to a plane.*
![**Figure 61.7**  *Using the dot product to get the distance from a
point to a plane.*](images/61-07.jpg)
Their approach is this: Think of rotation as projecting coordinates onto
new axes. That is, given that you have points in, say, worldspace,
@ -119,6 +117,5 @@ and that new tools, or new ways to use old tools, are Good Things. My
experience has been that rotation by projection, and dot product tricks
in general, offer those sorts of benefits for 3-D.
![](images/61-08.jpg)\
**Figure 61.8**  *Rotation to a new coordinate space by projection onto
new axes.*
![**Figure 61.8**  *Rotation to a new coordinate space by projection onto
new axes.*](images/61-08.jpg)