修改Koch曲线岛的迭代二叉树及分维测定

获得了修改Ｋｏｃｈ曲线岛周界和面积的迭代二叉树，并由之导出了周长和面积的表达式。说明周长—最大直径方法可获得该分形结构分维理论值，同时确定由周长—面积方法获得分维理论值和满足图象分析精度要求的理想分维值的临界嵌套层次及其同参量ａ和ｎ的关系，并认为在分维测定中周长—面积方法是可能得到理想分维值的有效方法。     

辐射度技术用于随机分维几何面的全局光照计算

分维几何为模拟自然体和景物提供了十分卓越的工具，然而，分维几何的造型是一个无限细分的随机造型过程，这就为分维几何的绘制带来了极大的困难，到目前为止，只有某些特殊的光线跟踪技术能够用于绘制分维几何曲面，主要产生高光效果。     

基于三维盒维数算法的城市分维计算

通过将传统的二维盒维数算法扩展到三维空间,提出了一个基于三维空间的盒维数计算方法。分别利用三维盒维数算法和二维盒维数算法计算城市的分维,通过对计算结果进行比较分析,观察到城市空间结构在第三维同样具有分形特征,证明传统城市分维计算中采用基于二维空间的分维算法或者简单地利用二维分维加1的方法表示三维分维都是不准确的,并进而给出正确的城市分维计算方法。     

更真实的分形自然景观模拟

本文利用分维在仿射变换下不变的性质，在保持统计特征不变（分维不变）的情况下，来处理自然现象的各向异性，从而给出自然现象的非均质性的一种模拟方法．本方法不仅可用于自然景现模拟也可用于地质储层等方面的模拟．     

基于ASTER-GDEM的延河流域水系分维特征分析

沟谷水系提取及分析，在描述地形骨架、获取构建分布式水文模型参数及研究地貌发展进程中有重要作用。传统的水系分维计算方法主要有量规法和栅格法， 本文将汇流阈值类比量规，遵照量规法的计算方法，研究流域的不同汇流，值得到不同的水系长度，分析其对数关系以计算水系的分维值。基于ASTER GDEM数据源， 以陕西省延河流域为例进行分析，其分维值为1.058；结合流域侵蚀积分曲线可知，延河流域水系侵蚀强烈。     

基于光谱曲线小波系数分维测度的高光谱影像高效分割方法

针对高光谱遥感影像处理效率的问题,提出了一种基于高光谱曲线小波分解低频系数分维特征影像和高频系数分维特征影像相结合的高光谱遥感影像分割方法。对高光谱响应曲线的分形测度进行了分析,提出基于光谱曲线小波分解高频系数的分维算法,得到多尺度高光谱分形特征影像。设计了低频系数分维特征影像和高频系数分维特征影像相结合的高光谱影像分割算法。高光谱曲线小波系数分维特征影像分割实验结果表明:该算法可取得与光谱曲线直接分形测度特征影像分割一致结果,但效率优于直接分维特征影像分割。     

城市住宅区遥感影像的分形特征研究

本文以分形理论和方法为基础，首先运用图像处理技术，对一幅上海城区彩红外航片扫描成像，并对住宅区分三类和８个区域进行了光谱数据采样。进而设计了粗视化求分维的算法和程序，分别从两个波段、两种采样方式计算获得了每一样区的４个分维数据。分析表明：住宅区影像的光谱曲线是一种典型的分形曲线，它们的分维值有效地反映了各类住宅区的图像结构特征。本研究揭示了城市住宅区遥感影像的分形特征提取可以进一步应用于住宅区的建设、规划和管理等定量指标估算。     

测量分维的“数盒子”算法研究

在分析传统“数盒子”算法测量分形体分维缺陷的基础上，首先通过引入一个新的参数η，提出了一种新的“数盒子”算法；然后通过具体算例，证实了该算法较传统算法的优越性，并且指出了它的局限性，同时还对“数盒子”算法测量的不确定性进行了讨论，进而提出了可行的提高测量精度的方法；最后应用平面激光诱发荧光（PLIF）技术得到了圆柱尾流区域的浓度场图象，并由此提取得到尾流紊动-非紊动界面，接着应用改进的算法对这一分界面的分维进行了测量，测量结果与前人的结论相吻合，并且发现，在非恒定流动中，分维数具有几乎不随时间而改变的特性。     

基于分维图形的研究及其应用

本文介绍了分形和分维基本理论,系统地研究了一般分维图、曼德布罗特图和分维布朗图的绘制过程及其应用领域,给出了在微机上绘制的各种相应的分维图形。     

分形分维在遥感图像纹理分析中的应用

基于分形几何学的影像纹理分类是以影像纹理的分维值为最基本的分类依据,影像分维值不同则属于不同的纹理类型。介绍了三种计算影像分维值的算法和数学模型,应用结果表明,综合运用三种方法进行纹理分析能得到满意的结果。     

人脸的层次化描述模型及识别研究

人脸自动识别是一个困难但有重要意义的工作。文中提出了一种基于人脸层次化描述的识别方法。该方法首先对人脸进行快速准确的特征定位及标准化,然后采用主元分析神经网络分别对定位的人脸及其特征区域进行最佳特征提取,从而得到人脸在低分辨率和较高分辨率上的两层特征描述用以识别,具有识别率高、特征数据量适中、可用于大量人像识别等特点。此方法在１３００幅人像上进行了测试,结果表明其在人脸转动、表情变化或入脸未经训练     

多模板ASM方法及其在人脸特征点检测中的应用

ASM(active shape model)是目前最流行的人脸对齐方法之一.为提高ASM在非均匀光照下多表情的人脸特征点检测的准确率,提出了一种融入Gabor特征、并将局部ASM和全局ASM结合的多模板ASM方法.人脸有丰富的表情,如微笑、惊讶、生气、发呆等等.就眼睛而言,可分为睁眼和闭眼;就嘴巴而言,可分为张大的嘴、微笑的嘴、O型的嘴(惊讶时)和紧闭的嘴.眼睛的这两种状态以及嘴巴的这4种状态使得形状有较大的非线性变化,不能简单地放在同一个线性模型下处理.分别对眼睛建立两个局部模板,对嘴巴建立4个局部模板,以及对整脸建立全局模板.在给定眼睛两个内眼角和嘴巴两个外嘴角的前提下,新方法首先用全局模板粗略确定眼睛所在区域,然后在此区域用眼睛的两个局部模板以及Hausdorff距离判断眼睛状态,同理可检测嘴巴状态,最后调用相应的全局模板去搜索整脸轮廓.实验表明,提出的方法其检测准确率比标准ASM有明显提高.     

基于单幅图像的人脸三维姿态估计

针对单张人像的三维姿态计算,结合面貌测量和射影几何的理论提出了一种方法：首先在人面部的平面区域内,选取眼角点,口角点,鼻翼点建立人脸模型;然后根据人脸平面上两个相互垂直的特征线投影到照片上的灭点位置,求出人脸平面的旋转方向。该方法特征点易于标定,且无需任何的辅助设备和先验知识,具有一定的实用性。     

基于人脸特征的摄影物距计算方法

针对从人像中计算摄影物距，结合面貌测量和射影几何的理论提出了一种方法：首先在人面部的平面区域内，选取眼角点、口角点、鼻翼点建立人脸模型，然后根据面部特征点的分布规律和投影原理，在照片平面与三维人脸位置之间建立起对应关系，最后利用面貌测量的统计知识求解出摄影的物距。这种方法无需任何辅助设备，易于实现，具有一定的实用性     

Eye detection in a facial image under pose variation based on multi-scale iris shape feature

The accurate location of eyes in a facial image is important to many human facial recognition-related applications, and has attracted considerable research interest in computer vision. However, most prevalent methods are based on the frontal pose of the face, where applying them to non-frontal poses can yield erroneous results.In this paper, we propose an eye detection method that can locate the eyes in facial images captured at various head poses. Our proposed method consists of two stages: eye candidate detection and eye candidate verification. In eye candidate detection, eye candidates are obtained by using multi-scale iris shape features and integral image. The size of the iris in face images varies as the head pose changes, and the proposed multi-scale iris shape feature method can detect the eyes in such cases. Since it utilizes the integral image, its computational cost is relatively low. The extracted eye candidates are then verified in the eye candidate verification stage using a support vector machine (SVM) based on the feature-level fusion of a histogram of oriented gradients (HOG) and cell mean intensity features.We tested the performance of the proposed method using the Chinese Academy of Sciences' Pose, Expression, Accessories, and Lighting (CAS-PEAL) database and the Pointing'04 database. The results confirmed the superiority of our method over the conventional Haar-like detector and two hybrid eye detectors under relatively extreme head pose variations.     

Facial feature detection using distance vector fields

A novel method for eye and mouth detection and eye center and mouth corner localization, based on geometrical information is presented in this paper. First, a face detector is applied to detect the facial region, and the edge map of this region is calculated. The distance vector field of the face is extracted by assigning to every facial image pixel a vector pointing to the closest edge pixel. The x and y components of these vectors are used to detect the eyes and mouth regions. Luminance information is used for eye center localization, after removing unwanted effects, such as specular highlights, whereas the hue channel of the lip area is used for the detection of the mouth corners. The proposed method has been tested on the XM2VTS and BioID databases, with very good results.     

一种彩色证件照片的眼角和嘴角定位方法

基于彩色标准学生证件,提出一种简单,有效的眼角和嘴角定位方法。首先,对图像进行亮度调整,颜色空间转换等预处理,再根据YCbCr空间中人脸肤色的聚类特性,分割出肤色区域,并利用数学形态学操作进行处理,最后,利用人脸的结构特征和几何分布规则,在小范围内准确定位眼角和嘴角的位置。实验结果表明,对于有噪声的,存在一定表情的图像,该方法具有较高的定位准确率,并且算法实现简单。     

Robust and Rapid Generation of Animated Faces from Video Images: A Model-Based Modeling Approach

We have developed an easy-to-use and cost-effective system to construct textured 3D animated face models from videos with minimal user interaction. This is a particularly challenging task for faces due to a lack of prominent textures. We develop a robust system by following a model-based approach: we make full use of generic knowledge of faces in head motion determination, head tracking, model fitting, and multiple-view bundle adjustment. Our system first takes, with an ordinary video camera, images of a face of a person sitting in front of the camera turning their head from one side to the other. After five manual clicks on two images to indicate the position of the eye corners, nose tip and mouth corners, the system automatically generates a realistic looking 3D human head model that can be animated immediately (different poses, facial expressions and talking). A user, with a PC and a video camera, can use our system to generate his/her face model in a few minutes. The face model can then be imported in his/her favorite game, and the user sees themselves and their friends take part in the game they are playing. We have demonstrated the system on a laptop computer live at many events, and constructed face models for hundreds of people. It works robustly under various environment settings.     

An effective method for detecting facial features and face in human-robot interaction

In this paper, an effective method of facial features detection is proposed for human-robot interaction (HRI). Considering the mobility of mobile robot, it is inevitable that any vision system for a mobile robot is bound to be faced with various imaging conditions such as pose variations, illumination changes, and cluttered backgrounds. To detecting face correctly under such difficult conditions, we focus on the local intensity pattern of the facial features. The characteristics of relatively dark and directionally different pattern can provide robust clues for detecting facial features. Based on this observation, we suggest a new directional template for detecting the major facial features, namely the two eyes and the mouth. By applying this template to a facial image, we can make a new convolved image, which we refer to as the edge-like blob map. One distinctive characteristic of this map image is that it provides the local and directional convolution values for each image pixel, which makes it easier to construct the candidate blobs of the major facial features without the information of facial boundary. Then, these candidates are filtered using the conditions associated with the spatial relationship of the two eyes and the mouth, and the face detection process is completed by applying appearance-based facial templates to the refined facial features. The overall detection results obtained with various color images and gray-level face database images demonstrate the usefulness of the proposed method in HRI applications.     

图像代数特征在面部表情识别中的应用

探讨了图像代数特征在面部表情识别中的应用,首先对面部表情图像进行了分割,得到眼睛和嘴巴区域,然后分别对眼睛和嘴巴区域提取不变矩和奇异值特征向量,并进行Fisher线性判别分析,最后训练了支持向量机分类器。实验结果表明该方法取得了比较好的识别效果。