UCSD CSE 167  Clipping & Scan Conversion (47 pages)
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Clipping & Scan Conversion
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 Pages:
 47
 School:
 University of California, San Diego
 Course:
 Cse 167  Computer Graphics
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Clipping Scan Conversion CSE167 Computer Graphics Instructor Steve Rotenberg UCSD Fall 2005 Project 2 Render a 3D hand made up of individual boxes using hierarchical transformations push pop The hand should perform some simple motion such as opening and closing the fingers Enable some basic lighting Use object oriented classes for Model like project 1 Hand Finger if you want Camera Light Example Yaw A spaceship is floating out in space with a matrix W The pilot wants to turn the ship 10 degrees to the left yaw Show how to modify W to achieve this Example Yaw We rotate W around its own b vector using the arbitrary axis rotation matrix In addition we pivot the rotation about the object s position d vector M T W d R a W b 10 T W d W M W where Ra a a x2 c 1 a x2 a x a y 1 c a z s a x a z 1 c a y s 0 a x a y 1 c a z s a y2 c 1 a y2 a x a z 1 c a y s a y a z 1 c a x s a y a z 1 c a x s a z2 c 1 a z2 0 0 0 0 0 1 Triangle Rendering The main stages in the traditional graphics pipeline are Transform Lighting Clipping Culling Scan Conversion Pixel Rendering Transformation In the transformation stage vertices are transformed from their original defining object space through a series of steps into a final 2 5D device space of actual pixels 1 v 4 D P C W v v x v y v v w v w v D v v z v w Transformation Step 1 v 4D P C W v 1 v The original vertex in object space W Matrix that transforms object into world space C Matrix that transforms camera into world space C 1 will transform from world space to camera space P Non affine perspective projection matrix v Transformed vertex in 4D un normalized viewing space Note sometimes this step is broken into two or more steps This is often done so that lighting and clipping computations can be done in camera space before applying the non affine transformation Transformation Step 2 v x v v w v y v w v z v w In the next step we map points from 4D space into our normalized viewing space called image space which ranges from 1 to 1 in x y and z From
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