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首页> 外文期刊>ACM Transactions on Graphics >Projection defocus analysis for scene capture and image display
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Projection defocus analysis for scene capture and image display

机译:投影散焦分析,用于场景捕获和图像显示

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摘要

In order to produce bright images, projectors have large apertures and hence narrow depths of field. In this paper, we present methods for robust scene capture and enhanced image display based on projection defocus analysis. We model a projector's defocus using a linear system. This model is used to develop a novel temporal defocus analysis method to recover depth at each camera pixel by estimating the parameters of its projection defocus kernel in frequency domain. Compared to most depth recovery methods, our approach is more accurate near depth discontinuities. Furthermore, by using a coaxial projector-camera system, we ensure that depth is computed at all camera pixels, without any missing parts. We show that the recovered scene geometry can be used for refocus synthesis and for depth-based image composition. Using the same projector defocus model and estimation technique, we also propose a defocus compensation method that filters a projection image in a spatially-varying, depth-dependent manner to minimize its defocus blur after it is projected onto the scene. This method effectively increases the depth of field of a projector without modifying its optics. Finally, we present an algorithm that exploits projector defocus to reduce the strong pixelation artifacts produced by digital projectors, while preserving the quality of the projected image. We have experimentally verified each of our methods using real scenes.
机译:为了产生明亮的图像,投影仪具有较大的光圈,因此景深较窄。在本文中,我们提出了基于投影散焦分析的鲁棒场景捕获和增强图像显示方法。我们使用线性系统对投影机的散焦进行建模。该模型用于开发一种新颖的时间散焦分析方法,以通过在频域中估计其投影散焦内核的参数来恢复每个相机像素的深度。与大多数深度恢复方法相比,我们的方法在深度深度不连续性方面更准确。此外,通过使用同轴投影仪-摄像机系统,我们确保在所有摄像机像素上都可以计算深度,而不会丢失任何部分。我们表明,恢复的场景几何可用于重新对焦合成和基于深度的图像合成。使用相同的投影仪散焦模型和估计技术,我们还提出了一种散焦补偿方法,该方法可以根据空间变化,深度相关的方式对投影图像进行过滤,以最大程度地减少其散焦模糊,并将其投影到场景上。该方法有效地增加了投影仪的景深,而无需修改其光学器件。最后,我们提出了一种算法,该算法可利用投影仪的散焦来减少数字投影仪产生的强烈像素化伪影,同时保留投影图像的质量。我们已经使用真实场景通过实验验证了每种方法。

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