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Hierarchical back-face computation

机译:分层背面计算

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We present a sub-linear algorithm to compute the set of back-facing polygons in a polyhedral model. The algorithm partitions the model into hierarchical clusters based on the orientations and positions of the polygons. As a preprocessing step, the algorithm constructs spatial decompositions with respect to each cluster. For a sequence of back-face computations, the algorithm exploits the coherence in view-point movement to efficiently determine whether it is in front of or behind a cluster. Due to coherence, the algorithm's expected running time is linear in the number of clusters on average. We have applied this algorithm to speed up the rendering of polyhedral models. On average, we are able to cull about 40/100 of the polygons. The algorithm accounts for 5 of the total CPU time per frame on an SGI Onyx. The overall frame rate is improved by 40-75/100 as compared to the standard back-face culling implemented in hardware. We also present an extension of our back-face computation algorithm to determine silhouettes of polygonal models. Our technique finds true perspective silhouettes by collecting edges at the common boundaries of back-facing and front-facing clusters.
机译:我们提出了一种亚线性算法来计算多面体模型中的一组背面多边形。该算法根据多边形的方向和位置将模型划分为层次聚类。作为预处理步骤,该算法针对每个聚类构造空间分解。对于一系列背面计算,该算法利用视点移动中的连贯性来有效地确定其是位于群集之前还是之后。由于相干性,该算法的预期运行时间在平均簇数上是线性的。我们已将此算法应用于加快多面体模型的渲染。平均而言,我们能够剔除大约40/100的多边形。该算法占SGI Onyx每帧总CPU时间的5。与硬件中实现的标准背面剔除相比,总体帧速率提高了40-75 / 100。我们还提出了背面计算算法的扩展,以确定多边形模型的轮廓。我们的技术通过收集背面和正面簇的公共边界处的边缘来找到真实的透视轮廓。

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