Fast example-based surface texture synthesis via discrete optimization

We synthesize and animate general texture patterns over arbitrary 3D mesh surfaces. The animation is controlled by flow fields over the target mesh, and the texture can be arbitrary user input as long it satisfies the Markov-Random-Field assumptions. We achieve this by extending the texture optimization framework over 3D mesh surfaces. We propose an efficient discrete solver inspired by k-coherence search, allowing interactive flow texture animation while avoiding the blurry blending problem for the least square solver in previous work. Our technique has potential applications ranging from simulation, visualization, and special effects.     

Texture evolution: 3D texture synthesis from single 2D growable texture pattern

An efficient model-independent 3D texture synthesis algorithm based on texture growing and texture turbulence is presented to create vivid 3D solid texture from a single 2D growable texture pattern. Given a 2D texture pattern of some growable material, our technique is able to create an anisotropic 3D volumetric texture cube to simulate the evolution of the material in 3D. An effective tiling scheme is designed to save computation and storage costs. Target objects are directly dipped into the synthesized 3D texture volume to generate creative, sculpture-like models that can be visualized with interactive speed. Our method is conceptually intuitive, computationally fast, and storage efficient compared with other solid texturing methods. As opposed to conventional 2D texture mapping work on polygonal surfaces, our approach is capable of decorating 3D point-rendering systems seamlessly. Furthermore, our combination of texture turbulence and texture growing techniques provides an attractive way to synthesize and tile natural 2D texture patterns, or generate simple but interesting motion textures.     

基于纹理合成的水墨山水画自动绘制

通过分析中国山水画的一般创作技法,提出了基于纹理合成的水墨山水画绘制方法.将一幅图像作为控制图像,用于控制要绘制的区域轮廓和明暗色调;采集画家的手稿作为样本图像,通过纹理合成绘制出国画绘画中的各种皴、染笔触;在传统的纹理合成方法上,提出了一种目标控制的多级纹理合成算法,该算法能利用控制图像有效地控制纹理合成的结果.从而可以将一幅数字照片或简单的手绘图自动地转换成各种中国水墨画效果的图像.仿真结果证明了该方法对于各种山水画的绘制具有良好的效果.     

Efficient texture synthesis using strict Wang Tiles

Wang Tiles are constructed from four texture samples, arranged so they can always match a choice of other tiles at two edges. Because they are precomputed, Wang Tiles are a very efficient way to generate textures on the fly. But matching problems occur within tiles and at the corners of adjacent tiles. By replacing the edge-matching texture samples with a new sample in the center of the tile, and using the graph cut path-finding algorithm, we overcome these problems and introduce additional texture diversity. Our s-Wang Tiles are a stricter interpretation of the original Wang Tile design, and our tile set is also smaller than that required by ω-Tiles: only eight different tiles are required for a non-repetitive titling.     

一种基于纹理合成的高效图像填充方法

为了更好地解决图像填充与修复问题,提出了一种基于图像样本纹理合成的新方法。该方法提出了一种新的定义像素点优先级的思路,来确定待填充区域的填充顺序,以此来保证处理结果的质量。相较于其他图像填充算法,该算法无需复杂的数学模型和大量的计算过程,从而提高了运算速度。实验证明,该方法不仅在处理效率上取得了很大进步,而且输出图像的质量也取得了理想效果。     

Spatial context-dependent multi-scale and directional image texture

This study evaluated image texture within a multi-scale context. The multi-scale texture profile is a representation of texture as a function of scale. It is related to the variogram, but has the advantage of being a direct measure of local texture over a specified kernel. Directional texture is a method to capture the dependence of texture on orientation using 1-dimensional kernels, and is potentially useful for quantifying texture for classes with a linear shape, such as roads or rivers. Seven derived texture attributes were proposed from the multi-scale texture profile and directional texture: the minimum, median, mean, maximum, range, minimum directional, and minimum multi-scale and directional texture. The derived texture attributes were found to be useful in developing a locally adaptive texture measure, which uses different texture attributes for different locations in the image. In order to develop the rules for the adaptive method, seven characteristic multi-scale texture profiles were identified. Rules were established to identify the general classes, and each pixel was assigned to one class only, depending on that pixel's texture profile. Optimal texture measures were proposed for each class. In an analysis using selected texture classes from IKONOS test data from Jeju, Korea, it was found that compared to all other texture measures, the adaptive texture provided the highest average and minimum classification accuracy, as well as the second highest maximum accuracy (69%, 51% and 92%, respectively). In comparison, the best fixed size kernel, 11?×?11 pixels, had accuracies in the same categories of 68%, 38% and 87%, and the original panchromatic image band had accuracies of 41%, 5% and 92%. Future work is needed to enhance the texture rules, and apply the adaptive texture method to other scales of data.     

Feature- and region-based auto painting for 2D animation

This paper presents a novel approach to automating the entire coloring process in traditional cel animation production. A feature-based region-matching algorithm is proposed. It first matches a set of master frames to construct correspondences between regions in the master frames and extract a stable topology. The first frame of each scene is then colored based on the set of master frames. With the painted first frame and established stable topology, each region in subsequent frames is matched with regions in the previous frames and colored. Compared with other algorithms, our approach is able to handle bigger changes between frames and automatically color the first frame of each sequence.     

在点模型上实现三维纹理合成的算法

为了避免网格重建过程而直接在三维点采样表面上进行纹理合成,研究了在点模型上的三维纹理合成的算法。利用KDtree这种数据结构在离散采样点上构建点与点的邻域关系,通过投影和建立匹配窗得到每一个待合成纹理的点与样图的映射关系,根据映射关系在样图中找出与待定点纹理值最佳匹配的点。最后将该匹配点的纹理值赋给待定点,同时结合邻域关系实现多点同时赋值。实验结果表明,该算法能有效地保持了生成的纹理结构和视觉效果的连续性和平滑性,具有耗时短、灵活可控、较好的鲁棒性等特点。     

结合三维几何形状信息和二维纹理的3D目标匹配

为了实现场景中三维目标与模型之间的匹配,提出了一种结合三维几何形状信息和二维纹理的三维目标匹配方法。首先提取场景中深度图像的尺度不变特征变换(SIFT)特征,用SIFT算法与三维模型重建时所用到的一系列2.5维深度图像进行一一匹配,找到与场景中目标姿态最为相似的深度图像,提取此深度图像的三维几何形状特征与模型进行匹配,实现模型的初始化,即将模型重置到与场景目标相接近的姿态。最后用融合二维纹理信息的迭代就近点（ICP）算法实现场景中目标与模型之间的匹配,从而得到场景中三维目标的准确姿态。实验结果验证了方法的可行性与精确性。