Path tracing is now the standard method used to generate realistic imagery in many domains, e.g., film, special effects, architecture etc. Path guiding has recently emerged as a powerful strategy to counter the notoriously long computation times required to render such images. We present a practical path guiding algorithm that performs product sampling, i.e., samples proportional to the product of the bidirectional scattering distribution function (BSDF) and incoming radiance. We use a spatial‐directional subdivision to represent incoming radiance, and introduce the use of Linearly Transformed Cosines (LTCs) to represent the BSDF during path guiding, thus enabling efficient product sampling. Despite the computational efficiency of LTCs, several optimizations are needed to make our method cost effective. In particular, we show how we can use vectorization, precomputation, as well as strategies to optimize multiple importance sampling and Russian roulette to improve performance. We evaluate our method on several scenes, demonstrating consistent improvement in efficiency compared to previous work, especially in scenes with significant glossy inter‐reflection.

中文翻译：

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使用线性变换余弦的实用产品路径引导

路径追踪现在是用于在许多领域（例如电影、特效、建筑等）生成逼真图像的标准方法。路径引导最近已成为一种强大的策略，以应对众所周知的渲染此类图像所需的长计算时间。我们提出了一种实用的路径引导算法，该算法执行产品采样，即与双向散射分布函数 (BSDF) 和入射辐射的乘积成正比的采样。我们使用空间方向细分来表示入射辐射，并在路径引导期间引入线性变换余弦 (LTC) 来表示 BSDF，从而实现高效的产品采样。尽管 LTC 的计算效率很高，但仍需要进行一些优化才能使我们的方法具有成本效益。特别是，我们展示了如何使用矢量化、预计算以及优化多重重要性采样和俄罗斯轮盘赌的策略来提高性能。我们在多个场景中评估了我们的方法，证明与之前的工作相比，效率持续提高，尤其是在具有显着光泽互反射的场景中。