Automatic facial expression recognition based on pixel‐pattern‐based texture feature

PCA, ICA, and Gabor wavelet are considered as the important and powerful face representation methods. In this article, we propose a new approach for face representation, which is called a pixel‐pattern‐based texture feature (PPBTF) and apply it to the real‐time facial expression recognition. A gray scale image is transformed into a pattern map where edges and lines are used for characterizing the facial texture information. Based on the pattern map, a feature vector is comprised of the numbers of the pixels belonging to each pattern. We use the image basis functions obtained by principal component analysis as the templates for pattern matching. Adaboost and Support Vector Machine are adopted to classify facial expression. Extensive experiments on the Cohn‐Kanade Database, PIE Database, and DUT Database illustrate that the PPBTF is quite effective and insensitive to illumination. The comparison with Gabor show the PPBTF is speedy. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 253–260, 2010     

Compressed sensing with MCT and I(2D)2PCA processing for efficient face recognition

This article describes an effective human face recognition algorithm. Even though the principle component analysis (PCA) is one of the most common feature extraction methods, it is not suitable to implement a real‐time embedded system for face recognition because large amount of computational load and memory capacity are necessary. To overcome this problem, we employ the incremental two‐directional two‐dimensional PCA (I(2D)²PCA) which is a combination of the (2D)²PCA to demand much less computational complexity than the conventional PCA and the incremental PCA (IPCA) to adapt the eigenspace only by using a new incoming sample datum without reusing of all the previous trained data. Furthermore, the modified census transform (MCT), a local normalization method useful for real‐world application and implementation in an embedded system, is adopted to address robustness to illumination variations. To achieve better recognition accuracy with less computational load, the processed features are classified by the compressive sensing approach using ?²–minimization. Experimental results on the Yale Face Database B show that the described system using the ?²–minimization‐based classification method for input data processed by the I(2D)²PCA and the MCT provided efficient and robust face recognition. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 133–139, 2013     

Surrogate modeling of 3D crack growth

This paper presents the development of a surrogate modeling technique for efficient non-planar fatigue crack growth analysis in mechanical components under multi-axial loading. Non-planar crack fronts are freely deformable space curves and require a high-dimensional representation. The large number of Cartesian co-ordinate variables involved in crack front representation makes it prohibitively expensive to train surrogate models for crack growth. Therefore, in our previous work, the crack shape was approximated using a planar parametrized representation. However, the parametrized representation limits the choice of crack shapes that can be considered. This paper presents the development of a non-parametric crack shape representation that allows for construction of a surrogate model for non-planar crack growth with complex crack shapes. The surrogate model is trained using a few runs of high-fidelity 3D simulations and predicts the evolution of a non-planar crack front under a given multi-axial, variable amplitude load history. We first parametrize the crack fronts as 3D spline curves with a fixed number of nodes. Instead of modeling the crack growth in this high dimensional data space, we project the data to a lower dimensional space using Principal Component Analysis (PCA) and then model the crack growth in this lower dimensional space. Finally, the predicted crack fronts are recovered using PCA back to the original data space. The proposed crack representation, growth modeling and recovery are illustrated using training points gathered from high-fidelity 3-D finite element simulations of non-planar crack growth in a cylindrical component similar to a rotorcraft mast, and the ability of the surrogate model to accurately predict the evolution of the crack growth over entire load histories is demonstrated.     

A virtual teleconferencing system based on face detection and 3D animation in a low‐bandwidth environment

In this article, we proposed a novel teleconferencing system that combines a facial muscle model and the techniques of face detection and facial feature extraction to synthesize a sequence of life‐like face animation. The proposed system can animate realistic 3D face images in a low‐bandwidth environment to support virtual videoconferencing. Based on the technique of feature extraction, a face detection algorithm for the virtual conferencing system is proposed in this article. In the proposed face detection algorithm, the YCbCr skin color model is used to detect the possible face area of the image; the feature points of the face is determined by using the symmetry property of the face and the gray level characteristics of the eyes and the mouth. According to the positions of the feature points on a facial image, we can compute the transformation values of the feature points. These values will then be sent via a network from the sender's side to the receiver's side frame by frame. We can synthesize the realistic facial animations on the receiver's side based on these. Experimental results show that the proposed system can achieve a practical animated face‐to‐face virtual conference with good facial expressions and a low‐bandwidth requirement. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 323–332, 2010     

Use of biomimetic hexagonal surface texture in friction against lubricated skin

Smooth contact pads that evolved in insects, amphibians and mammals to enhance the attachment abilities of the animals'' feet are often dressed with surface micropatterns of different shapes that act in the presence of a fluid secretion. One of the most striking surface patterns observed in contact pads of these animals is based on a hexagonal texture, which is recognized as a friction-oriented feature capable of suppressing both stick–slip and hydroplaning while enabling friction tuning. Here, we compare this design of natural friction surfaces to textures developed for working in similar conditions in disposable safety razors. When slid against lubricated human skin, the hexagonal surface texture is capable of generating about twice the friction of its technical competitors, which is related to it being much more effective at channelling of the lubricant fluid out of the contact zone. The draining channel shape and contact area fraction are found to be the most important geometrical parameters governing the fluid drainage rate.     

莱洛三角形微孔织构化端面密封性能数值模拟

基于微孔型表面织构在改善机械端面密封性能方面的优势,提出了一种新型的莱洛三角形微孔表面织构,并利用数值模拟方法考察了莱洛三角形微孔织构化端面的密封性能。首先,在动环表面上分别设置圆形、三角形、莱洛三角形三种微孔表面织构。然后,利用GAMBIT软件进行3种微孔织构化密封端面模型网格划分,利用Fluent软件分析密封端面的流场特性并获得其流场压力分布。最后,总结出3种微孔织构化密封端面的开启力、泄漏率和开漏比随织构面积率、孔深、密封间隙、操作压力及转速的变化规律。结果表明：3种微孔织构化密封端面的开启力和泄漏率随着密封参数的变化具有相同的变化规律;当S_p＝10%,h_d＝3～4 μm,h_p<3 μm,p_i<0.3 MPa时,3种微孔织构化密封端面均呈现出较好的密封性能;相比于圆形、三角形微孔织构化密封端面,莱洛三角形微孔织构化密封端面具有较大的开启力和较小的泄漏率,同时具有较大的开漏比。研究成果可为微孔织构化机械端面的密封参数优化设计提供参考。     

Recognition of interacting rotational and prismatic machining features from 3-D mill-turn parts

Current feature recognition methods generally recognize and classify machining features into two classes: rotational features and prismatic features. Based on the different characteristics of geometric shapes and machining methods, rotational features and prismatic features are recognized using different methods. Typically, rotational features are recognized using two-dimensional (2-D) edge and profile patterns. Prismatic features are recognized using 3-D geometric characteristics, for example, patterns in solid models such as 3-D face adjacency relationships. However, the current existing feature recognition methods cannot be applied directly to a class of so-called mill-turn parts where interactions between rotational and prismatic features exist. This paper extends the feature recognition domain to include this class of parts with interacting rotational and prismatic features. A new approach, called the machining volume generation method, is developed. The feature volumes are generated by sweeping boundary faces along a direction determined by the type of machining operation. Different types of machining features can be recognized by generating different forms of machining volumes using various machining operations. The generated machining volumes are then classified using face adjacency relationships of the bounding faces. The algorithms are executed in four steps, classification of faces, determining machining zones, generation of rotational machining volumes and prismatic machining volumes, and classification of features. The algorithms are implemented using the 3-D boundary representation data modelled on the ACIS solid modeller. Example parts are used to demonstrate the developed feature recognition method.     

An efficient memetic algorithm for 3D shape matching problems

Shape representation plays a vital role in any shape optimization exercise. The ability to identify a shape with good functional properties is dependent on the underlying shape representation scheme, the morphing mechanism and the efficiency of the optimization algorithm. This article presents a novel and efficient methodology for morphing 3D shapes via smart repair of control points. The repaired sequence of control points are subsequently used to define the 3D object using a B-spline surface representation. The control points are evolved within the framework of a memetic algorithm for greater efficiency. While the authors have already proposed an approach for 2D shape matching, this article extends it further to deal with 3D shape matching problems. Three 3D examples and a real customized 3D earplug design have been used as examples to illustrate the performance of the proposed approach and the effectiveness of the repair scheme. Complete details of the problems are presented for future work in this direction.     

Registration‐free monitoring of multimode near‐circular shape profiles

Traditional shape profile monitoring of product geometric features mostly focuses on one type or mode of shapes in the discrete‐part manufacturing. Little attention has been paid to monitoring of multimode shape profiles, where different modes of shapes appear in a sample in the batch production process. Motivated by a real example of a powder material production process, we exploit the statistical process monitoring of multimode near‐circular shape profiles. First, we develop a feature extraction approach that is invariant to shape rotation and thus requires no registration for a mixture of different modes of shape profiles. The extracted feature vectors capture shape features well, based on which different modes of shape profiles are separated into several clusters. This enables us to build a Gaussian mixture model for the multimodality in the feature vector space. In process surveillance, a control chart is constructed based on the likelihood ratio test for detecting shifts in both the proportions and the shape features of multimode near‐circular shape profiles. Numerical simulations and real case studies demonstrate the effectiveness of our proposed chart.     

A shape grammar for non-manifold modeling

Shape grammars offer a notationally rich representation for dealing with shapes defined over an algebra of points, lines, planes, and solids. Operations in the algebra are bound in subshape recognition and replacement, making them ideal candidates for design as formal solid modeling representations, and for manufacturing as shape-based feature recognizers. As well, given the topological hierarchy of the algebra of shapes, non-manifold modeling is clearly a fundamental part of shape grammars. Thus, one can work at the level of wireframe models, boundary models, and solid models. These characteristics make the shape grammars eminently suitable as a formal representation for both manifold and non-manifold representations of discrete shape.     

Relating intensities with three-dimensional facial shape using partial least squares

The authors apply partial least squares regression to predict three-dimensional (3D) face shape from a single image. PLS describes the relationship between independent (intensity images) and dependent (3D shape) variables by seeking directions in the space of independent variables that are associated with large variations in the space of dependent variables. We use this idea to construct statistical models of intensity and 3D shape that capture strongly linked variations in both spaces. This decomposition leads to the construction of two different models that capture common variations in 3D shape and intensity. Using the intensity model, a set of parameters is obtained from out-of-training intensity examples. These intensity parameters can then be used directly in the 3D shape model to approximate facial shape. Experiments show that prediction is achieved with reasonable accuracy, improving results obtained through canonical correlation analysis.     

A 3D modeling and free‐view generation system using environmental stereo cameras

We propose a 3D video system that uses environmental stereo cameras to display a target object from an arbitrary viewpoint. This system is composed of the following stages: image acquisition, foreground segmentation, depth field estimation, 3D modeling from depth and shape information, and arbitrary view rendering. To create 3D models from captured 2D image pairs, a real‐time segmentation algorithm, a fast depth reconstruction algorithm, and a simple and efficient shape reconstruction method were developed. For viewpoint generation, the 3D surface model is rotated toward the desired place and orientation, and the texture data extracted from the original camera is projected onto this surface. Finally, a real‐time system that demonstrates the use of the aforementioned algorithms was implemented. The generated 3D object can easily be manipulated, e.g., rotated or translated, to render images from different viewpoints. This provides stable scenes of a minimal area that made it possible to understand the target space, and also made it easier for viewers to understand in near real‐time. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 367–378, 2007     

A fast algorithm for multifield representation and multiscale simulation of high‐quality 3D stochastic aggregate microstructures by concurrent coupling of stationary Gaussian and fractional Brownian random fields

This study presents a multiscale computational framework for the representation and generation of concrete aggregate microstructures on the basis of the multifield theory, which couples the stationary Gaussian random field with the fractional Brownian random field. Specifically, the stationary Gaussian field is utilized to simulate the morphological shape of an aggregate on the coarse scale, whereas the surface topography of the aggregate on the fine scale is represented by the fractional Brownian field. To bridge the 2 scales, a concurrent coupling formula is proposed. This coupled technique allows for smooth transition between the coarse and fine scales and permits the rapid generation of highly realistic concrete aggregates that can be tailored to the desired quality and requirements, making the algorithm computationally appealing. In the generation of the random fields on the 2 scales, the Fourier representation of block circulant covariance matrices with circulant blocks is exploited, which yields substantial efficiency advantages over the conventional Cholesky decomposition approach in factorizing covariance matrices as well as simulating random fields. Meanwhile, a microsurface postprocessing and reconstruction procedure is also developed to convert the generated random fields into realistic 3D shapes. The numerical methodology proposed in this study offers tremendous potential for a plethora of applications in cement‐based materials.     

Veridicality of three-dimensional shape perception predicted from amplitude spectra of natural textures

We show that the amplitude spectrum of a texture pattern, regardless of its phase spectrum, can be used to predict whether the pattern will convey the veridical three-dimensional (3-D) shape of the surface on which it lies. Patterns from the Brodatz collection of natural textures were overlaid on a flat surface that was then corrugated in depth and projected in perspective. Perceived ordinal shapes, reconstructed from a series of local relative depth judgments, showed that only about a third of the patterns conveyed veridical shape. The phase structure of each pattern was then randomized. Simulated concavities and convexities were presented for both the Brodatz and the phase-randomized patterns in a global shape identification task. The concordance between the shapes perceived from the Brodatz patterns and their phase-randomized versions was 80-88%, showing that the capacity for a pattern to correctly convey concavities and convexities is independent of phase information and that the amplitude spectrum contains all the information required to determine whether a pattern will convey veridical 3-D shape. A measure of the discrete oriented energy centered on the axis of maximum curvature was successful in identifying textures that convey veridical shape.     

采用小波框架的纺织品缺陷分类方法

针对纺织品缺陷分类,提出了一种基于判别小波框架的分类方法.该方法采用小波框架来描述纺织品图像的多尺度纹理特性,并设计与纺织品缺陷纹理相对应的小波框架函数来替代标准小波函数,来更有效地描述各类缺陷纹理的内在结构差异.在判别特征提取训练方法框架下,通过将小波框架函数和分类器两者的设计相联合,来实现缺陷分类错误概率的最小化.对8类纺织品缺陷的466个样本,以及434个无缺陷样本进行了分类实验,获得了95.8%的分类准确率.     

DVE中按需预取的递进纹理数据传输方法

很多虚拟环境中的3D模型具有高质量的表面纹理。因此，在大的分布式虚拟环境的应用系统中需要传输大量的纹理数据。然而，分布式虚拟环境中大规模的纹理数据传输带来的传输延时令影响系统的真实感和实时性。为解决这个问题用拉普拉斯金字塔算法和哈尔变换算法实现了纹理递进传输。实验结果和测试数据表明，这两种算法都有效地减少了初始传输延时。但是拉普拉斯金字塔算法增加了表示一幅纹理贴图所需的数据量，而哈尔变换算法则保持数据量不变。为了进一步减轻网络负载，可以用均匀标量量化和行程编码等算法进一步减少在此DVE系统中的所需传输的数据总量。     

一种基于GPU实现的自适应八叉树纹理绘画算法

当前,虽然基于二维图像映射定义的传统二维纹理已得到广泛应用。但是它有很多局限性。这是因为很多三维模型在纹理空间中进行参数化是非常困难的,例如隐式表面、细分表面和高密度或高细节的多边形网格。基于八叉树纹理定义,提出了一种新型的自适应八叉树纹理绘画算法。和传统的八叉树纹理映射算法相比,不但占用更少的存储空间,而且实现了基于GPU的纹理查询,有更快的查找速度。     

Contemporary technologies for 3D digitization of Maori and Pacific Island artifacts

Three‐dimensional (3D) digitization is a key aspect in the preservation and exhibition of museum artifacts. The objective of this article is to investigate contemporary technologies for creating accurate 3D digital models of artifacts from the Maori and Pacific heritage and to establish a generic digitization methodology so that the 3D models can be archived and exhibited both over the internet and within museum displays. This process involves procedures for selecting artifacts that are suitable for laser scanning and then setting up the artifact for scanning. This is followed by the actual scanning and postprocessing stages. To achieve this, the Polhemus FastSCAN laser scanner has been used to collect raw point cloud surface data from artifacts of various sizes, shapes, textures, colors, and materials. The article explains the generic steps developed for postprocessing of raw scan data in the form of a cloud of geometric data points to a completely rendered 3D model with colors mapped on to the model. These generic steps involve removal of background noise, enhancement of texture, filling of holes, merging of separate scans, and color mapping. The results from the scanning and postprocessing of a wahaika, (a Maori club‐like weapon) and a Polynesian stone pounder reveal that it is important to use a scanner that is flexible enough to capture all the surface information irrespective of the artifact's geometry, and one with the capability of capturing color information with high accuracy. © 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 244–259, 2009     

Independent Component Analysis–Based Feature Extraction Technique for Defect Classification Applied for Pulsed Eddy Current NDE

With the development of nondestructive detection, the emerging testing techniques provide new challenges to signal analysis and interpretation approach applied to the inspection evaluation. Some researchers have developed the methods that focus on feature analysis of detected signals. This article presents a new feature analysis by the Independent Component Analysis (ICA) approach to evaluate the defects tested by the pulsed eddy current (PEC) technique. ICA is a high-order statistics technique used to separate multi-unknown sources, which has been successfully applied to facial image identification and separation of the components of 1D signal. In this article, the ICA approach is utilized to project the response signals of various defects into the independent components (ICs) feature subspace by signal representation model. Dependent on the selected ICs, each defect is represented by different projected coefficients, which are proposed to discriminate and classify the defects that belong to three categories. The improved ICA model is proposed to improve the classification of two similar categories of single defects: metal loss and subsurface defects. The evaluation using the series of experimental data has validated the classification of single defects and the defects with lift-off effect by our ICA approach. The comparison with Principal component analysis (PCA)–based approach further verified the better performance of the ICA-based model.     

Numerical assessment of springback for the deep drawing process by level set interpolation using shape manifolds

In this paper, we introduce an original shape representation approach for post-springback characterization based on the automatic generation of parameterized level set functions. The central idea is the concept of the shape manifold representing the design domain in the reduced-order shape-space. Performing Proper Orthogonal Decomposition on the shapes followed by using the Diffuse Approximation allows us to efficiently reduce the problem dimensionality and to interpolate uniquely between admissible input shapes, while also determining the smallest number of parameters needed to characterize the final formed shape. We apply this methodology to the problem of springback assessment for the deep drawing operation of metal sheets.