Simulating Wood Using a Voxel Approach

In this paper we present a technique for generating three-dimensional wood textures using a regular texture array. Currently three-dimensional wood textures are generated using procedural textures. Procedural textures are flexible and require little memory, however the modeling of local artifacts such as knots is difficult using the procedural approach. By representing the wood as a texture array and growing the wood in this array we can easily simulate local phenomena such as knots. Our growth model is an approximation to the biological model and assumes that there are several similar wood cells per array element. This means that we can model artifacts that are defined by groups of similar cells. In particular our model is well suited for the modeling of soft-woods.     

Spectrum-based synthesis of vibrotactile stimuli: active footstep display for crinkle of fragile structures

When a human crinkles or scrunches a fragile object, for which the yield force is very small that it is hardly perceived, they identify the material of the object based on tactile stimuli delivered to the skin. In addition, humans are able to recognize materials even when they are crinkled at different speeds. In order to realize these human recognition features of the crinkle of a fragile object, we develop a vibrotactile synthesis method. This method synthesizes the vibrotactile acceleration stimuli in response to a crinkle speed based on the preliminarily measured acceleration spectra. Using this method, we develop an active footstep display that presents a virtual crinkle of fragile structures made of different materials to its users. Experimental participants could identify three of the four types of virtual structure materials at rates significantly higher than the chance level. The four materials were copy and typing paper, aluminum foil, and polypropylene film. Furthermore, the trends of answer ratios exhibit good correspondence with those for the real cylindrical fragile objects. We conclude that the developed method is valid for the virtual crinkle of fragile structures and will enhance the validity of virtual reality systems, such as a virtual walkthrough system.     

Haptic texture generation using stochastic models and teleoperation

In this paper, a method is suggested to generate haptic textures for isotropic surfaces using stochastic models. A Master-Slave tele-haptic system was realized by using two PHANToMs. Moving the stylus of the Master PHANToM by a user caused the Slave to scratch the surface of objects such as sandpaper or printing paper. Force data, generated by using the error between the Master and the Slave positions, were recorded and served as measures of the texture of the object in the remote environment. An estimate of haptic texture was obtained after a simple dynamic compensation of the force data. The haptic texture was modeled using a filter that was designed by analyzing the power-spectrum of estimated texture data. By passing White Gaussian Noise through the filter, virtual texture data could be generated. The forces corresponding to the virtual texture and the real texture by teleoperation were individually delivered through the Master PHANToM to users who were asked to identify or discriminate the corresponding textures. The users?? responses show that the virtual modeled textures were quite similar to the real ones.     

振动触觉纹理再现技术研究综述

纹理力触觉再现是通过特定的硬件装置模拟产生与物体纹理表面接触时的触感，使用户能感受到物体的粗糙度、软硬度等纹理特征信息。振动刺激作为再现物体触觉信息的一种刺激方式，在纹理触觉再现中被广泛运用，产生了不同的振动触觉表达装置和纹理触觉表达方法。从纹理触觉认知的角度，阐述了人对振动刺激的触觉感知生理学基础；介绍了纹理触觉再现的原理和方法；从振动与纹理特征的映射方法以及振动刺激方式两个方面分析了目前振动触觉纹理再现技术的发展现状；最后对相关研究的发展进行了总结展望。     

A Subjective Evaluation of Texture Synthesis Methods

This paper presents the results of a user study which quantifies the relative and absolute quality of example‐based texture synthesis algorithms. In order to allow such evaluation, a list of texture properties is compiled, and a minimal representative set of textures is selected to cover these. Six texture synthesis methods are compared against each other and a reference on a selection of twelve textures by non‐expert participants (N = 67). Results demonstrate certain algorithms successfully solve the problem of texture synthesis for certain textures, but there are no satisfactory results for other types of texture properties. The presented textures and results make it possible for future work to be subjectively compared, thus facilitating the development of future texture synthesis methods.     

An empirical evaluation of different haptic feedback for shape and texture recognition

The scope of this research is to evaluate three different haptic feedback methods for texture discrimination in virtual environments. In particular, a Phantom force feedback device, a custom-made vibrotactile dataglove and paper palpable prototypes have been used. This paper describes a new study which corroborates the results of an initial experiment (Martínez et al. in 2011 International Conference on Cyberworlds, pp. 62–68, 2011) and performs a more in-depth evaluation of some results of interest and, in particular, those based on gender. In the experiment expansion, the number of users has been increased, so both genders are even, and the texture identification strategies have been analyzed. Finally, statistical analyses have been conducted to assess the differences between both genders, showing a new path which could be explored with new experiments. In addition, the vibrotactile dataglove has proved to have a notable behavior in the detection of varying grating textures, and it is even useful to identify shapes.     

Deformation-based interactive texture design using energy optimization

In this paper, we present a novel interactive texture design scheme based on deformation and energy optimization. Given a small sample texture, the design process starts with applying a set of deformation operations to the sample texture to obtain a set of deformed textures. Then local changes to those deformed textures are further made by replacing their local regions with the texture elements interactively selected from other textures. Such a deform–select–replace process is iterated many times until the desired deformed textures are obtained. Finally the deformed textures are composed to form a large texture with graph-cut optimization. By combining the graph-cut algorithm with an energy optimization process, interactive selections of local texture elements are done simply through indicating the positions of texture elements very roughly with a brush tool. Our experimental results demonstrate that the proposed technique can be used for designing a large variety of versatile textures from a single small sample texture, increasing or decreasing the density of texture elements, as well as for synthesizing textures from multiple sources.     

The Promise and Perils of Near-Regular Texture

Motivated by the low structural fidelity for near-regular textures in current texture synthesis algorithms, we propose and implement an alternative texture synthesis method for near-regular texture. We view such textures as statistical departures from regular patterns and argue that a thorough understanding of their structures in terms of their translation symmetries can enhance existing methods of texture synthesis. We demonstrate the perils of texture synthesis for near-regular texture and the promise of faithfully preserving the regularity as well as the randomness in a near-regular texture sample.     

Material Space Texturing

Many objects have patterns that vary in appearance at different surface locations. We say that these are differences in  materials,  and we present a  material-space  approach for interactively designing such textures. At the heart of our approach is a new method to pre-calculate and use a 3D texture tile that is periodic in the spatial dimensions ( s ,  t ) and that also has a material axis along which the materials change smoothly. Given two textures and their feature masks, our algorithm produces such a tile in two steps. The first step resolves the features morphing by a level set advection approach, improved to ensure convergence. The second step performs the texture synthesis at each slice in material-space, constrained by the morphed feature masks. With such tiles, our system lets a user interactively place and edit textures on a surface, and in particular, allows the user to specify which material appears at given positions on the object. Additional operations include changing the scale and orientation of the texture. We support these operations by using a global surface parameterization that is closely related to quad re-meshing. Re-parameterization is performed on-the-fly whenever the user's constraints are modified.     

High quality solid texture synthesis using position and index histogram matching

The synthesis quality is one of the most important aspects in solid texture synthesis algorithms. In recent years several methods are proposed to generate high quality solid textures. However, these existing methods often suffer from the synthesis artifacts such as blurring, missing texture structures, introducing aberrant voxel colors, and so on. In this paper, we introduce a novel algorithm for synthesizing high quality solid textures from 2D exemplars. We first analyze the relevant factors for further improvements of the synthesis quality, and then adopt an optimization framework with the k-coherence search and the discrete solver for solid texture synthesis. The texture optimization approach is integrated with two new kinds of histogram matching methods, position and index histogram matching, which effectively cause the global statistics of the synthesized solid textures to match those of the exemplars. Experimental results show that our algorithm outperforms or at least is comparable to the previous solid texture synthesis algorithms in terms of the synthesis quality.     

Texture mixing and texture movie synthesis using statisticallearning

We present an algorithm based on statistical learning for synthesizing static and time-varying textures matching the appearance of an input texture. Our algorithm is general and automatic and it works well on various types of textures, including 1D sound textures, 2D texture images, and 3D texture movies. The same method is also used to generate 2D texture mixtures that simultaneously capture the appearance of a number of different input textures. In our approach, input textures are treated as sample signals generated by a stochastic process. We first construct a tree representing a hierarchical multiscale transform of the signal using wavelets. From this tree, new random trees are generated by learning and sampling the conditional probabilities of the paths in the original tree. Transformation of these random trees back into signals results in new random textures. In the case of 2D texture synthesis, our algorithm produces results that are generally as good as or better than those produced by previously described methods in this field. For texture mixtures, our results are better and more general than those produced by earlier methods. For texture movies, we present the first algorithm that is able to automatically generate movie clips of dynamic phenomena such as waterfalls, fire flames, a school of jellyfish, a crowd of people, etc. Our results indicate that the proposed technique is effective and robust     

Texturing Internal Surfaces from a Few Cross Sections

We introduce a new appearance-modeling paradigm for synthesizing the internal structure of a 3D model from photographs of a few cross-sections of a real object. When the internal surfaces of the 3D model are revealed as it is cut, carved, or simply clipped, we synthesize their texture from the input photographs. Our texture synthesis algorithm is best classified as a morphing technique, which efficiently outputs the texture attributes of each surface point on demand. For determining source points and their weights in the morphing algorithm, we propose an interpolation domain based on BSP trees that naturally resembles planar splitting of real objects. In the context of the interpolation domain, we define efficient warping and morphing operations that allow for real-time synthesis of textures. Overall, our modeling paradigm, together with its realization through our texture morphing algorithm, allow users to author 3D models that reveal highly realistic internal surfaces in a variety of artistic flavors.     

Anisotropic Solid Texture Synthesis Using Orthogonal 2D Views

Analytical approaches, based on digitised 2D texture models, for an automatic solid (3D) texture synthesis have been recently introduced to Computer Graphics. However, these approaches cannot provide satisfactory solutions in the usual case of natural anisotropic textures (wood grain for example). Indeed, solid texture synthesis requires particular care, and sometimes external knowledge to "guess" the internal structure of solid textures because only 2D texture models are used for analysis. By making some basic assumptions about the internal structure of solid textures, we propose a very efficient method based on a hybrid analysis (spectral and histogram) for an automatic synthesis of solid textures. This new method allows us to obtain high precision solid textures (closely resembling initial models) in a large number of cases, including the difficult case of anisotropic textures.     

Textures for realistic image synthesis

An important aspect in generating images of real materials and surfaces is the contribution of the visual effects of textures. This study presents methods for simulating a variety of different textures.Two general types of texture, geometric and spectral, are simulated. Geometric textures incorporate the irregularities and variations which can be found in the shape and form of real surfaces. Spectral textures involve variations of the properties of materials which cause the absorption of specific wavelengths of light.An integrated system for image synthesis which is based on ray tracing is used as the testbed for the texturing research. Previous methods of texturing are adapted by ray tracing, and some new methods for simulating heterogeneous materials are presented.     

基于比例模板和边界校正的皮革图像分割

利用纹理特征进行智能化分割是提高皮革生产效率和产品质量的有效手段。为此提出了一种基于比例模板和区域边界校正的皮革图像分割方法，该方法首先根据皮革各部位所占面积比例的经验知识构造一个比例模板，并以此模板将图像粗分割成若干个区域，然后利用自相关函数分布统计出每个区域边界点所在窗口内的平均纹理周期，并与区域内窗口平均纹理周期进行相似比较，依据预设的平均纹理周期相似度阈值对区域边界点进行判别校正，使得每一区域内的平均纹理周期误差在允许的范围内保持一致。仿真试验表明，该方法简单易行，能有效地分割皮革图像。     

Toward realistic haptic rendering of surface textures

New sophisticated haptic-rendering algorithms let users experience virtual objects through touch. We systematically investigate the unrealistic behavior of virtual haptic textures. The emerging science of haptic rendering consists of delivering properties of physical objects through the sense of touch. Owing to the recent development of sophisticated haptic-rendering algorithms, users can now experience virtual objects through touch in many exciting applications, including surgical simulations, virtual prototyping, and data perceptualization. Haptics holds great promise to enrich the sensory attributes of virtual objects that these systems can produce. One area that has received increasing attention in the haptics community is haptic texture rendering, the goal of which is to introduce micro-geometry-scale features on object surfaces. Haptic objects rendered without textures usually feel smooth, and sometimes slippery. Appropriate haptic textures superimposed on haptic objects enhance an object's realism.     

Wearable vibrotactile systems for virtual contact and information display

This paper presents a development history of a wearable, scalable vibrotactile stimulus delivery system. This history has followed a path from desktop-based, fully wired systems, through hybrid approaches consisting of a wireless connection from the host computer to a body-worn control box and wires to each tactor, to a completely wireless system employing Bluetooth technology to connect directly from the host to each individual tactor unit. Applications for such a system include delivering vibrotactile contact cues to users of virtual environments, providing directional cues in order to increase situational awareness in both real and virtual environments, and for general information display in wearable contexts. Through empirical study, we show that even a simple configuration, such as eight tactors arrayed around the torso, can be effective in increasing situational awareness in a building-clearing task, compared to users who perform the same task without the added cues.     

A Wavelet-Based Approach for Analyzing Industrial Stochastic Textures With Applications

Several continuous manufacturing processes use stochastic texture images for quality control and monitoring. Large amounts of pictorial data are acquired, providing important information about both the materials produced and the manufacturing processes involved. However, it is often difficult to measure objectively the similarity among industrial stochastic images or to discriminate between texture images of stochastic materials with distinct properties. Nowadays, the degree of discrimination required by industrial processes often goes beyond the limits of human visual perception. This paper proposes to model this specific class of textures as colored noise and presents a new approach for multiresolution stochastic texture representation and discrimination in industry (e.g., nonwoven textiles and paper). The wavelet transform is used to represent stochastic texture images in multiple resolutions and to describe them using local orientation and density variability as features. Based on this representation, a multiresolution distance measure for stochastic textures is proposed, and industrial applications of the method and experimental results are reported. The conclusions include ideas for future work     

Sobel算子在衣物纹理类型检测中的应用研究

衣物纹理是指衣物表面的纹络现象。在越来越发达的智能图像处理过程中,针对衣物纹理的检测也变得愈发平常,人们期望能够使用计算机自动识别衣物表面的纹理类型,如横竖条纹、方格及碎花等,从而进行基于纹理类型的相应操作。文中提出了一种利用Sobel算子进行梯度方向统计来实现衣物纹理类型检测的方法,其中对各纹理类型的判定依据来源于实验分析过程,经测试表明,该方法及相应判定依据能够有效地检测出衣物常见的纹理类型。     

Texture boundary detection based on the long correlation model

The problem of detecting texture boundaries without assuming any knowledge on the number of regions or the types of textures is considered. Texture boundaries are often regarded as better features than intensity edges, because a large class of images can be considered a composite of several different texture regions. An algorithm is developed that detects texture boundaries at reasonably high resolution without assuming any prior knowledge on the texture composition of the image. The algorithm utilizes the long correlation texture model with a small number of parameters to characterize textures. The parameters of the model are estimated by a least-squares method in the frequency domain. The existence and the location of texture boundary is estimated by the maximum-likelihood method. The algorithm is applied to several different images, and its performance is shown by examples. Experimental results show that the algorithm successfully detects texture boundaries without knowing the number of types of textures in the image