Brooks Stephen
Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada.
IEEE Trans Vis Comput Graph. 2007 Sep-Oct;13(5):1041-54. doi: 10.1109/TVCG.2007.1025.
This paper presents a technique for mixed media non-photorealistic painting and portraiture. The goal of this work is to transform digital images into renderings that approximate the appearance of mixed media artwork, which incorporates two or more traditional visual media. We achieve this by first separating an input image into distinct regions based on the degree of local detail present in the image. Each region is then processed independently with a user-selected NPR filter. This allows the user to treat highly detailed regions differently from regions of low frequency content. The separately processed regions are then smoothly fused in the gradient domain. In addition, we extend our work to the rendering of mixed media portraits. Portraits pose unique challenges that we address with our method of segmentation, which is based on a composite of face detection and image detail. Our approach offers the user a great deal of flexibility over the end result, while at the same time requiring very little input. This input takes the form of a few simple and discrete choices. The results demonstrate an impressive array of transformational possibilities.
本文提出了一种用于混合媒体非真实感绘画和肖像画的技术。这项工作的目标是将数字图像转换为近似混合媒体艺术品外观的渲染图,混合媒体艺术品包含两种或更多传统视觉媒体。我们通过首先根据图像中存在的局部细节程度将输入图像分离成不同区域来实现这一目标。然后使用用户选择的非真实感渲染(NPR)滤镜对每个区域进行独立处理。这允许用户以不同方式处理高细节区域和低频内容区域。然后在梯度域中将单独处理的区域平滑融合。此外,我们将工作扩展到混合媒体肖像的渲染。肖像画带来了独特的挑战,我们通过基于面部检测和图像细节合成的分割方法来解决这些挑战。我们的方法为用户提供了对最终结果的极大灵活性,同时只需很少的输入。这种输入采用一些简单且离散的选择形式。结果展示了一系列令人印象深刻的变换可能性。