We present a probabilistic model of how viewers may use defocus blur in conjunction with other pictorial cues to estimate the absolute distances to objects in a scene. Our model explains how the pattern of blur in an image together with relative depth cues indicates the apparent scale of the image's contents. From the model, we develop a semiautomated algorithm that applies blur to a sharply rendered image and thereby changes the apparent distance and scale of the scene's contents. To examine the correspondence between the model/algorithm and actual viewer experience, we conducted an experiment with human viewers and compared their estimates of absolute distance to the model's predictions. We did this for images with geometrically correct blur due to defocus and for images with commonly used approximations to the correct blur. The agreement between the experimental data and model predictions was excellent. The model predicts that some approximations should work well and that others should not. Human viewers responded to the various types of blur in much the way the model predicts. The model and algorithm allow one to manipulate blur precisely and to achieve the desired perceived scale efficiently.

中文翻译：

---

使用模糊来影响感知距离和大小


我们提出了一个概率模型，说明观看者如何将散焦模糊与其他图像线索结合使用来估计到场景中物体的绝对距离。我们的模型解释了图像中的模糊模式与相对深度线索如何指示图像内容的表观比例。根据该模型，我们开发了一种半自动算法，该算法将模糊应用于清晰渲染的图像，从而改变场景内容的视距和比例。为了检查模型/算法与实际观看者体验之间的对应关系，我们对人类观看者进行了实验，并将他们对绝对距离的估计与模型的预测进行了比较。我们对由于散焦而具有几何正确模糊的图像以及具有常用的正确模糊近似值的图像执行了此操作。实验数据和模型预测之间的一致性非常好。该模型预测某些近似值应该可以很好地工作，而其他近似值则不能。人类观众对各种类型的模糊的反应与模型预测的方式大致相同。该模型和算法允许人们精确地操纵模糊并有效地实现所需的感知尺度。