Age estimation using a hierarchical classifier based on global and local facial features

The research related to age estimation using face images has become increasingly important, due to the fact it has a variety of potentially useful applications. An age estimation system is generally composed of aging feature extraction and feature classification; both of which are important in order to improve the performance. For the aging feature extraction, the hybrid features, which are a combination of global and local features, have received a great deal of attention, because this method can compensate for defects found in individual global and local features. As for feature classification, the hierarchical classifier, which is composed of an age group classification (e.g. the class of less than 20 years old, the class of 20-39 years old, etc.) and a detailed age estimation (e.g. 17, 23 years old, etc.), provide a much better performance than other methods. However, both the hybrid features and hierarchical classifier methods have only been studied independently and no research combining them has yet been conducted in the previous works. Consequently, we propose a new age estimation method using a hierarchical classifier method based on both global and local facial features. Our research is novel in the following three ways, compared to the previous works. Firstly, age estimation accuracy is greatly improved through a combination of the proposed hybrid features and the hierarchical classifier. Secondly, new local feature extraction methods are proposed in order to improve the performance of the hybrid features. The wrinkle feature is extracted using a set of region specific Gabor filters, each of which is designed based on the regional direction of the wrinkles, and the skin feature is extracted using a local binary pattern (LBP), capable of extracting the detailed textures of skin. Thirdly, the improved hierarchical classifier is based on a support vector machine (SVM) and a support vector regression (SVR). To reduce the error propagation of the hierarchical classifier, each age group classifier is designed so that the age range to be estimated is overlapped by consideration of false acceptance error (FAE) and false rejection error (FRE) of each classifier. The experimental results showed that the performance of the proposed method was superior to that of the previous methods when using the BERC, PAL and FG-Net aging databases.     

基于局部纹理特征的沥青路面裂缝检测方法

针对不均匀光照和阴影等因素影响沥青路面图像中裂缝检测误识别问题,提出一种基于局部纹理特征的沥青路面裂缝检测方法.设计结构保持型Retinex算法将高频的纹理信号从低频光照信号和结构型纹理中分离,改进百分比阈值算法,获取高信噪比的裂缝区域二值图像,建立高置信裂缝段的特征匹配机制,利用圆形度、面积、不同置信裂缝的类间欧氏距...     

Automatic age estimation based on facial aging patterns

While recognition of most facial variations, such as identity, expression and gender, has been extensively studied, automatic age estimation has rarely been explored. In contrast to other facial variations, aging variation presents several unique characteristics which make age estimation a challenging task. This paper proposes an automatic age estimation method named AGES (AGing pattErn Subspace). The basic idea is to model the aging pattern, which is defined as the sequence of a particular individual' s face images sorted in time order, by constructing a representative subspace. The proper aging pattern for a previously unseen face image is determined by the projection in the subspace that can reconstruct the face image with minimum reconstruction error, while the position of the face image in that aging pattern will then indicate its age. In the experiments, AGES and its variants are compared with the limited existing age estimation methods (WAS and AAS) and some well-established classification methods (kNN, BP, C4.5, and SVM). Moreover, a comparison with human perception ability on age is conducted. It is interesting to note that the performance of AGES is not only significantly better than that of all the other algorithms, but also comparable to that of the human observers.     

A new texture representation approach based on local feature saliency

Although it has been studied in some depth, texture characterization is still a challenging issue for real-life applications. In this study, we propose a multiresolution salient-point-based approach in the wavelet domain. This incorporates a two-phase feature extraction scheme. In the first phase, each wavelet subband (LH, HL, or HH) is used to compute local features by using multidisciplined (statistical, geometrical, or fractal) existing texture measures. These features are converted into binary images, called salient point images (SPIs), via threshold operation. This operation is the key step in our approach because it provides an opportunity for better segmentation and combination of multiple features. In the final phase, we propose a set of new texture features, namely, salient-point density (SPD), non-salient-point density (NSPD), salient-point residual (SPR), saliency and non-saliency product (SNP), and salient-point distribution non-uniformity (SPDN). These features characterize various aspects of image texture such as fineness/coarseness, primitive distribution, internal structures, etc. These features are then applied to the well-known K-means algorithm for unsupervised segmentation of texture images. Experimental results with the standard texture (Brodatz) and natural images demonstrate the robustness and potential of the proposed features compared to the wavelet energy (WE) and local extrema density feature (LED). The text was submitted by the authors in English. Md. Khayrul Bashar was born in Chittagong, Bangladesh in 1969. He received his B.E. (1993), M.Tech. (1998), and PhD (2004) degrees from Bangladesh University of Engineering and Technology (BUET), Indian Institute of Technology (IIT) Bombay, and Nagoya University, respectively. He was a research engineer from 1995 to 1999 at Bangladesh Space Research and Remote Sensing Organization (SPARRSO) and assistant professor from 1999 to 2000 at the department of Electrical and Electronic Engineering, Chittagong University of Engineering and Technology (CUET), Bangladesh. Since 2004, he has been a research fellow in the department of Information Engineering, Nagoya University, Japan. Dr. Bashar is a member of IEEE, IEICE, BCS, and IEB. His research interest includes developing algorithms for image understanding, content-based image retrieval and web-application design, analysis and testing. Noboru Ohnishi was born in Aichi, Japan in 1951. He received his B.E., M.E., and PhD degrees in Electrical Engineering from Nagoya University in 1973, 1975, and 1984, respectively. From 1975–1986, he worked as a researcher in the Rehabilitation Engineering centre under the Ministry of Labor, Japan. In 1986, he joined as an Assistant Professor in the dept. of Electrical Engineering of Nagoya University. Currently, he is a professor of the dept. of Information Engineering at the same university. During his long professional life, he has also served as a visiting researcher (1992–1993) in the laboratory of artificial intelligence at Michigan University, and team leader (1993–2001) at the Bio-mimetic Control Research Center, RIKEN, Nagoya, Japan. He also holds many respectable positions at various professional bodies in Japan and he has published many research papers (more than 140) in various international journals. For his technical creativity and ingenuity, he was awarded SICE society prizes in 1996 and 1999. His research interest includes brain analysis, modeling, and brain support, computer vision, and audition. He is a member of IEEE, IPSJ, IEICE, IEEJ, IIITE, JNNS, SICE and RSJ. Kiyoshi Agusa received his PhD degree in computer science from Kyoto University in 1982. Currently, he is a professor of the department of Information Systems, Graduate School of Information Science, Nagoya University. His research area includes software engineering, program repository, and software reuse. Since 2003, he has been working as a team leader of a university-industry collaboration project entitled “e-Society,” which is a part of the “e-Japan” project, and doing research on reliability issues for web-based applications. He is a member of IPSJ, ISSST, IEICE, ACM and IEEE.     

基于人脸图像的性别识别与年龄估计

针对以往利用人脸图像单方面进行性别识别或年龄估计,提出了利用公共特征、私有特征同时进行性别识别与年龄估计.用对光照、尺度变化具有很强鲁棒性的Gabor小波变换提取人脸特征.降维后的有效人脸特征分成公共特征、私有特征两部分,公共特征用于性别识别,私有特征进行年龄估计.在FG-NET人脸库及自建OFID人脸库中用RBF神经网络进行了实验,取得了良好效果.     

将局部二进制模式应用于动态纹理识别的新方法

动态纹理的处理、描述与识别是纹理分析的热门领域。动态纹理是对普通纹理在时间域方面的扩展,包括动态特征和静态特征。基于LBP算法的扩展提出的VLBP算法较好的描述了动态纹理特征,但是计算量过大,模板过多。本文提出了一种由VLBP算法改进的基于局部二进制运动模式的特征提取方法用以动态纹理的描述和识别,它包括提取动态特征和提取静态特征两部分。将LBP算子做为块匹配准则提取局部二进制运动模式柱状图做为动态特征的描述,提取LBP柱状图做为静态特征的描述,并将二者连接得出描述动态纹理特征的联合的局部二进制运动模式柱状图。通过对DynTex集实验的结果表明,本文提出的方法在性能和识别率方面均要优于VLBP。     

A new approach for texture segmentation based on NBP method

Nowadays, image processing is an interesting research area due to the growth of the communication technologies. Matching problem, which consists of localizing one texture in an image, that contains several textures is one of the fundamental problem of image processing and pattern recognition. In this paper, a new feature extraction method and texture segmentation system are proposed. The proposed method (RINBP) is robust against rotation and improves the ability of extracting the local information. The segmentation architecture follows several steps. First, fixing a converging point α. After that, a Main analysis Window (MW) starting from α to the bottom left corner of the image is determined. Then, several possible windows are extracted and the feature extraction method is applied on each window. Finally, a similarity measure is calculated in order to decide if this window is pertinent or not. This process is stopped until the size of the MW reaches a minimum size. Each pertinent window increases the relevance of the desired texture in the output image. Finally, an image of relevance is obtained by considering the most relevant area. For the experiments, textured images generated from Brodatz album database are used. The experiments have shown the superiority of our method compared to other existing methods. The obtained results have illustrated the robustness and the efficiency of the proposed segmentation method based on the relevance of the analysis windows.     

A multi-scale and multi-orientation image retrieval method based on rotation-invariant texture features

Texture retrieval is a vital branch of content-based image retrieval.Rotation-invariant texture retrieval plays a key role in texture retrieval.This paper addresses three major issues in rotation-invariant texture retrieval: how to select the texture measurement methods,how to alleviate the influence of rotation for texture retrieval and how to apply the proper multi-scale analysis theory for texture images.First,the spectrum influence between a Radon transform and a Log-polar transform was compared after t...     

基于旋转不变纹理特征的多尺度多方向图像渐进检索

纹理检索是基于内容图像检索的重要内容,旋转不变纹理图像检索是实现纹理检索的关键途径之一.针对旋转不变纹理图像检索中需要解决的3个关键问题:如何消除旋转影响、如何选择多尺度分析方法以及如何构造和度量纹理特征矢量,本文分别分析了Radon变换和Log-polar变换在消除旋转位移时对频谱的影响,以及NSCT变换和小波变换在不同检索参数下的平均检索性能,在此基础上构造出多尺度多方向纹理变换谱和旋转不变特征矢量,提出一种多尺度多方向旋转不变纹理图像渐进检索方法.这种方法采用了可顾及人类视觉对纹理能量敏感性的相似性度量标准,分别采用旋转位移处理后的NSCT变换域低频子带和高通子带实现纹理图像的粗检索和精细检索.Brodatz标准纹理图像库的检索实验表明,本文提出的利用多尺度多方向纹理变换谱构造旋转不变特征矢量的方法既可获取纹理主方向,同时又能有效地表征纹理细节信息,两级渐进式检索策略与多尺度分析方法相结合,既能提高旋转不变纹理图像检索的查准率,又能保证较高的检索效率.     

Emotion recognition using facial expression by fusing key points descriptor and texture features

Multimedia Tools and Applications - Emotions have a great significance in human-to-human and in human-to-computer communication and interaction. In this paper, an effective and novel approach to...     

Reliable facial expression recognition for multi-scale images using weber local binary image based cosine transform features

Multimedia Tools and Applications - Accurate recognition of facial expression is a challenging problem especially from multi-scale and multi orientation face images. In this article, we propose a...     

基于局部纹理ASM模型的人脸表情识别

针对主动形状模型(ASM)迭代过程容易陷入局部最优解的不足,提出了一种基于局部纹理模型的改进ASM算法,即EWASM.在局部纹理模型构建中,以每个特征点的中垂线方向搜索其邻域信息以确定最佳匹配位置,对衡量匹配程度的马氏距离加以推广,进而得到改进的扩展加权局部纹理模型,它由中心局部纹理模型、前局部纹理模型和后局部纹理模型共3个子模型加权组成,并对加权参数进行实验优化,使各个特征点之间的联系更加紧密,模型的鲁棒性更好.通过表情识别实验对提出的EWASM算法和传统ASM算法进行对比,选用RBF神经网络分类器进行表情分类,实验结果表明EWASM算法收敛速度更快,识别率也得以提高,并解决了局部最小问题,能更有效地表征表情.     

An auxiliary gaze point estimation method based on facial normal

Considering the main disadvantage of the existing gaze point estimation methods which restrict user’s head movement and have potential injury on eyes, we propose a gaze point estimation method based on facial normal and binocular vision. Firstly, we calibrate stereo cameras to determine the extrinsic and intrinsic parameters of the cameras; Secondly, face is quickly detected by Viola–Jones framework and the center position of the two irises can be located based on integro-differential operators; The two nostrils and mouth are detected based on the saturation difference and their 2D coordinates can be calculated; Thirdly, the 3D coordinates of these five points are obtained by stereo matching and 3D reconstruction; After that, a plane fitting algorithm based on least squares is adopted to get the approximate facial plane, then, the normal via the midpoint of the two pupils can be figured out; Finally, the point-of-gaze can be obtained by getting the intersection point of the facial normal and the computer screen. Experimental results confirm the accuracy and robustness of the proposed method.     

用于重叠峰分辨的卡尔曼滤波法

导数法广泛应用于重叠峰分辨,但信噪比会随着导数阶数的增加而降低。提出一种基于卡尔曼滤波的导数方法,可以显著提高高阶导数谱的信噪比,提高重叠峰分辨力。另外,该方法不需要建立数学模型,计算简便,能满足手持式仪器实时性要求。用仿真数据研究了该法在重叠峰分辨中对信噪比的影响,以离子迁移率谱图分辨为例说明了该法的实际应用。     

A new method for expiration code detection and recognition using gabor features based collaborative representation

Text in images and video contains important information for visual content understanding, indexing, and recognizing. Extraction of this information involves preprocessing, localization and extraction of the text from a given image. In this paper, we propose a novel expiration code detection and recognition algorithm by using Gabor features and collaborative representation based classification. The proposed system consists of four steps: expiration code location, character isolation, Gabor features extraction and characters recognition. For expiration code detection, the Gabor energy (GE) and the maximum energy difference (MED) are extracted. The performance of the recognition algorithm is tested over three Gabor features: GE, magnitude response (MR) and imaginary response (IR). The Gabor features are classified based on collaborative representation based classifier (GCRC). To encompass all frequencies and orientations, downsampling and principal component analysis (PCA) are applied in order to reduce the features space dimensionality. The effectiveness of the proposed localization algorithm is highlighted and compared with other existing methods. Extensive testing shows that the suggested detection scheme outperforms existing methods in terms of detection rate for large image database. Also, GCRC show very competitive results compared with Gabor feature sparse representation based classification (GSRC). Also, the proposed system outperforms the nearest neighbor (NN) classifier and the collaborative representation based classification (CRC).     

Off-line signature verification based on grey level information using texture features

A method for conducting off-line handwritten signature verification is described. It works at the global image level and measures the grey level variations in the image using statistical texture features. The co-occurrence matrix and local binary pattern are analysed and used as features. This method begins with a proposed background removal. A histogram is also processed to reduce the influence of different writing ink pens used by signers. Genuine samples and random forgeries have been used to train an SVM model and random and skilled forgeries have been used for testing it. Results are reasonable according to the state-of-the-art and approaches that use the same two databases: MCYT-75 and GPDS-100 Corpuses. The combination of the proposed features and those proposed by other authors, based on geometric information, also promises improvements in performance.