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Potentially Visible Sets are used to accelerate the rendering of 3D environments. This is a form of occlusion culling, whereby a candidate set of ''potentially visible'' polygons are pre-computed, then indexed at run-time in order to quickly obtain an estimate of the visible geometry. The term ''PVS'' is sometimes used to refer to any occlusion culling algorithm (since in effect, this is what all occlusion algorithms compute), although in almost all the literature, it is used to refer specifically to occlusion culling algorithms that pre-compute visible sets and associate these sets with regions in space. In order to make this association, the camera view-space (the set of points from which the camera can render an image) is typically subdivided into (usually convex) regions and a PVS is computed for each region. == Benefits vs. Cost == The benefit of offloading visibility as a pre-process are: * The application just has to look up the pre-computed set given its view position. This set may be further reduced via frustum culling. Computationally, this is far cheaper than computing occlusion based visibility every frame. * Within a frame, time is limited. Only 1/60th of a second (assuming a 60 Hz frame-rate) is available for visibility determination, rendering preparation (assuming graphics hardware), AI, physics, or whatever other app specific code is required. In contrast, the offline pre-processing of a potentially visible set can take as long as required in order to compute accurate visibility. The disadvantages are: * There are additional storage requirements for the PVS data. * Preprocessing times may be long or inconvenient. * Can't be used for completely dynamic scenes. * The visible set for a region can in some cases be much larger than for a point. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Potentially visible set」の詳細全文を読む スポンサード リンク
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