Documents

Hidden Surface Removal1

Description
Hidden Surface Lines
Categories
Published
of 35
All materials on our website are shared by users. If you have any questions about copyright issues, please report us to resolve them. We are always happy to assist you.
Related Documents
Share
Transcript
  1 Hidden Surface Removal  ã Goal: Determine which surfaces are visible and which are not. ã Z-Buffer is just one of many hidden surface removal algorithms. ã Other names: ã Visible-surface detection ã Hidden-surface elimination ã Display all  visible surfaces, do not display any  occluded surfaces. ã We can categorize into ã Object-space methods ã Image-space methods  2 Hidden Surface Elimination  ã Object space algorithms: determine which objects are in front of others  ãResize doesn’t require recalculation   ã Works for static scenes ã May be difficult to determine  ã Image space algorithms: determine which object is visible at each pixel ã Resize requires recalculation ã Works for dynamic scenes  Hidden Surface Elimination Complexity ã If a scene has n  surfaces, then since every surfaces may have to be tested against every other surface for visibility, we might expect an object precision algorithm to take O(n 2   )  time. ã On the other hand, if there are N   pixels, we might expect an image precision algorithm to take O(nN)  time, since every pixel may have to be tested for the visibility of n  surfaces. ã Since the number of the number of surfaces is much less than the number of pixels, then the number of decisions to be made is much fewer in the object precision case, n < < N. 3  Hidden Surface Elimination Complexity ã Different algorithms try to reduce these basic counts. ã Thus, one can consider bounding volumes (or “extents”) to determine roughly whether objects cannot overlap - this reduces the sorting time. With a good sorting algorithm, O(n 2   ) may be reducible to a more manageable O(n log n). ã Concepts such as depth coherence (the depth of a point on a surface may be predicable from the depth known at a nearby point) can cut down the number of arithmetic steps to be performed. ã Image precision algorithms may benefit from hardware acceleration. 4
We Need Your Support
Thank you for visiting our website and your interest in our free products and services. We are nonprofit website to share and download documents. To the running of this website, we need your help to support us.

Thanks to everyone for your continued support.

No, Thanks