**2**

# help calculating this

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#1
Members - Reputation: **103**

Posted 19 December 2012 - 12:05 PM

I attached a img with this post . Please consider the marked lines as a grid in a orthgonal projection . I want to select a tile in this grid by clicking mouse over them . i want to know what kind of a formula used to solve this kind of problem . please help me to solve this issue;Thanks in advance

john lin

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#2
Members - Reputation: **819**

Posted 19 December 2012 - 05:59 PM

In general steps:hi to all,

I attached a img with this post . Please consider the marked lines as a grid in a orthgonal projection . I want to select a tile in this grid by clicking mouse over them . i want to know what kind of a formula used to solve this kind of problem . please help me to solve this issue;Thanks in advance

john lin

1. Multiply your world-to-view (w2v) and view-to-projection (v2p) matrices to give you a world-to-projection matrix (w2p).

2. Calculate the inverse of this to give you a projection-to-world matrix (p2w)

3. Transform the projection-space position (where you clicked on screen in projection space coordinates) to a world position

4. Transform the projection-space direction (depending on your coordinate system... something like (0, 0, 1)) to a world direction

5. Do intersection tests from the world-space point and directions to the rectangles in the grid

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#4
Members - Reputation: **340**

Posted 19 December 2012 - 06:22 PM

I'm no big expert in vision, but my first try would be to use the Canny edge detector (or some scale space variant) to create a grid image. Then partition the regions image by building a trapezoidal map. After that's done you can answer point location queries efficiently.

Though even this simple scheme will require a lot of tweaking to work correctly.

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#5
Crossbones+ - Reputation: **9281**

Posted 19 December 2012 - 08:31 PM

The slowsort algorithm is a perfect illustration of the multiply and surrender paradigm, which is perhaps the single most important paradigm in the development of reluctant algorithms. The basic multiply and surrender strategy consists in replacing the problem at hand by two or more subproblems, each slightly simpler than the original, and continue multiplying subproblems and subsubproblems recursively in this fashion as long as possible. At some point the subproblems will all become so simple that their solution can no longer be postponed, and we will have to surrender. Experience shows that, in most cases, by the time this point is reached the total work will be substantially higher than what could have been wasted by a more direct approach.

- *Pessimal Algorithms and Simplexity Analysis*

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#7
Crossbones+ - Reputation: **13912**

Posted 20 December 2012 - 03:19 PM