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Visual attention for efficient high-fidelity graphics

机译:视觉注意力,带来高效的高保真图形

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High-fidelity rendering of complex scenes at interactive rates is one of the primary goals of computer graphics. Since high-fidelity rendering is computationally expensive, perceptual strategies such as visual attention have been explored to achieve this goal. In this paper we investigate how two models of human visual attention can be exploited in a selective rendering system. We examine their effects both individually, and in combination, through psychophysical experiments to measure savings in computation time while preserving the perceived visual quality for a task-related scene. We adapt the lighting simulation system Radiance to support selective rendering, by introducing a selective guidance system which can exploit attentional processes using an importance map. Our experiments demonstrate that viewers performing a visual task within the environment consistently fail to notice the difference between high quality and selectively rendered images, computed in a significantly reduced time.
机译:以交互速率高保真渲染复杂场景是计算机图形学的主要目标之一。由于高保真渲染的计算量很大,因此已探索了诸如视觉注意之类的感知策略来实现此目标。在本文中,我们研究了在选择性渲染系统中如何利用人类视觉注意力的两个模型。我们通过心理物理实验单独或组合检查它们的影响,以测量节省的计算时间,同时保留与任务相关的场景的感知视觉质量。我们通过引入选择性指导系统,使照明模拟系统 Radiance 适应支持选择性渲染,该系统可以使用重要性图利用注意力过程。实验表明,在环境中执行视觉任务的观看者始终无法注意到以明显减少的时间计算出的高质量图像和选择性渲染图像之间的差异。

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