Multi-resolution feature fusion for face recognition

For face recognition, image features are first extracted and then matched to those features in a gallery set. The amount of information and the effectiveness of the features used will determine the recognition performance. In this paper, we propose a novel face recognition approach using information about face images at higher and lower resolutions so as to enhance the information content of the features that are extracted and combined at different resolutions. As the features from different resolutions should closely correlate with each other, we employ the cascaded generalized canonical correlation analysis (GCCA) to fuse the information to form a single feature vector for face recognition. To improve the performance and efficiency, we also employ “Gabor-feature hallucination”, which predicts the high-resolution (HR) Gabor features from the Gabor features of a face image directly by local linear regression. We also extend the algorithm to low-resolution (LR) face recognition, in which the medium-resolution (MR) and HR Gabor features of a LR input image are estimated directly. The LR Gabor features and the predicted MR and HR Gabor features are then fused using GCCA for LR face recognition. Our algorithm can avoid having to perform the interpolation/super-resolution of face images and having to extract HR Gabor features. Experimental results show that the proposed methods have a superior recognition rate and are more efficient than traditional methods.     

General triangular midpoint subdivision

In this paper, we introduce triangular subdivision operators which are composed of a refinement operator and several averaging operators, where the refinement operator splits each triangle uniformly into four congruent triangles and in each averaging operation, every vertex will be replaced by a convex combination of itself and its neighboring vertices. These operators form an infinite class of triangular subdivision schemes including Loop's algorithm with a restricted parameter range and the midpoint schemes for triangular meshes. We analyze the smoothness of the resulting subdivision surfaces at their regular and extraordinary points by generalizing an established technique for analyzing midpoint subdivision on quadrilateral meshes. General triangular midpoint subdivision surfaces are smooth at all regular points and they are also smooth at extraordinary points under certain conditions. We show some general triangular subdivision surfaces and compare them with Loop subdivision surfaces.     

Total curvature variation fairing for medial axis regularization

We present a new fairing method for planar curves, which is particularly well suited for the regularization of the medial axis of a planar domain. It is based on the concept of total variation regularization. The original boundary (given as a closed B-spline curve or several such curves for multiply connected domains) is approximated by another curve that possesses a smaller number of curvature extrema. Consequently, the modified curve leads to a smaller number of branches of the medial axis. In order to compute the medial axis, we use the state-of-the-art algorithm from [1] which is based on arc spline approximation and a domain decomposition approach. We improve this algorithm by using a different decomposition strategy that allows to reduce the number of base cases from 13 to only 5. Moreover, the algorithm reduces the number of conic arcs in the output by approx. 50%.     

基于广义Hoek-Brown准则的节理岩体力学参数折剪计算

节理化岩体力学参数是矿山工程地质和稳定性分析的重要基础数据,一般在实验室通过单轴、三轴试验只能得到岩石的力学参数,无法得到岩体的力学参数。目前,利用岩石力学参数确定岩体力学参数的方法较多,但都过于烦琐或准确度不高,急需一种新的简易确定方法。因此,通过利用基于广义Hoek-Brown准则的地质强度指标（GSI法）,并结合相应的岩土分析软件,强度折剪岩石力学参数值,从而得到岩体的力学参数。通过将该方法应用于赤峰中色白音诺尔矿业有限公司岩体力学参数的计算中,证明采用该方法考虑岩体的结构面和完整性,可较为准确地反映节理化岩体的力学特性,且方便可行,具有工程实用价值。?     

一种广义分子计算模型及其在 NP问题中的应用

目前各种分子计算模型多基于生物技术,求解一个问题的分子计算机算法很难不作修改地应用于其他类似的问题,尚不似传统计算机般通用。为此,提出一种基于图灵机的广义分子计算模型,其由一台单带图灵机、一条单向只写带和一条工作带组成,通过只写带与工作带之间特殊的映射函数实现并行的同时读、写操作。实验说明了该模型能够在多项式时间求解NP完全的满足性问题（SAT）,比现有分子计算模型在计算准确性和通用性上存在明显优势。     

低分辨率人耳图像识别方法研究*

针对人耳识别中存储量和计算速度的要求,同时考虑远距离拍摄时低分辨率人耳识别问题,探讨了低分辨率人耳图像识别性能,给出了分辨率与识别率的关系。首先采用高斯金字塔对人耳图像进行不同层的分解,然后对每一层图像应用广义判别分析方法（GDA）提取特征,最后计算样本间的余弦距离,通过阈值法分类识别。实验结果表明,当人耳图像分辨率降低为36×24时系统识别性能最好,满足实时生物识别系统的要求。     

基于Petri网的信息流安全属性的分析与验证*

信息流安全属性的定义均基于不同的语义模型,很难作出比较,以Petri网作为描述安全系统的统一模型,在Petri网上定义四种常见的安全属性,并分析它们之间的逻辑关系。在信息流安全属性验证方面,传统的方法称为展开方法,该方法适用于确定型系统,而对于非确定型系统,该方法是可靠的,但不完备。进一步对Petri网上已经定义的四种属性给出可靠完备的验证算法,并开发出相应的验证工具。最后通过实例说明了验证方法在搜索隐通道方面的应用。     

广义KDV-MKDV方程的精确解

利用直接积分方法将广义KDV-MKDV方程化为一阶变系数非线性常微分方程组,然后用待定系数法确定相应的常数获得了广义KDV-MKDV方程新的精确解;利用先作假设变换后选取试探函数的方法来直接构造广义KDV-MKDV方程新的精确解.     

基于双CPU的太阳能跟踪系统的研究

从提高太阳能电池板的输出功率出发,提出了基于双CPU控制方式的太阳能跟踪系统。系统采用俯仰-水平双轴控制,以单片机STC12C2052AD为光电控制单元的核心处理器,以混合式步进电机为执行机构,以TMS320F2812为核心控制器件的三相正弦波细分驱动器实现了混合式步进电机的精确定位。实验表明系统运行稳定,具有很高的实用价值。