ISAR image scattering center association based on speeded-up robust features

Multimedia Tools and Applications - It is difficult for the imaging radar of the single antenna to correlate the scattering centers in 3D reconstruction. Therefore, an association method of...     

Retraction Note: Offline scripting-free author identification based on speeded-up robust features

International Journal on Document Analysis and Recognition (IJDAR) -     

基于MCD稳健估计的PCA人脸识别算法

针对人脸识别中,识别效果易受人脸修饰、部分遮挡、噪声干扰等不确定因素影响的问题,提出一种MCDPCA人脸识别算法以改进识别效果。基于主成分分析（PCA）进行特征脸提取,结合最小协方差行列式方法（MCD）进行异常点检测和抗噪。针对人脸图像使用MCD算法,求出稳健的协方差矩阵估计,基于此协方差估计矩阵使用PCA技术提取重要的人脸特征用于识别。实验结果表明,在有遮挡和噪声干扰的情况下,相比传统PCA方法,该方法明显提高了人脸图像识别率。     

基于快速鲁棒特征的CamShift跟踪算法

为了解决CamShift算法由于对颜色敏感导致的跟踪效果变差或失效的问题,提出一种基于局部特征匹配的CamShift跟踪算法。采用快速鲁棒特征(SURF)方法在多通道图像的目标区域和搜索区域提取包含图像信息的局部特征点,并利用近似最近邻搜索对特征点进行匹配;使用提纯后的匹配结果得到特征点的位置、尺度及方向信息,对CamShift方法进行约束和更新,以提高跟踪精度和稳定性。实验结果表明,与经典CamShift算法和同类的改进算法相比,该算法能够较好地实现对复杂背景下旋转和放缩运动目标的实时跟踪。     

A robust algorithm for template curve estimation based on manifold embedding

The problem of finding a template function that represents the common pattern of a sample of curves is considered. To address this issue, a novel algorithm based on a robust version of the isometric featuring mapping (Isomap) algorithm is developed. When the functional data lie on an unknown intrinsically low-dimensional smooth manifold, the corresponding empirical Fréchet median function is chosen as an intrinsic estimator of the template function. However, since the geodesic distance is unknown, it has to be estimated. For this, a version of the Isomap procedure is proposed, which has the advantage of being parameter free and easy to use. The feature estimated with this method appears to be a good pattern for the data, capturing the inner geometry of the curves. Comparisons with other methods, with both simulated and real datasets, are provided.     

一种基于BioHashing和洗牌算法的可撤销密钥绑定方案

针对传统加密方案中密钥管理困难的问题,提出了一个新的通过指纹管理密钥的密钥绑定方案。该方案通过BioHashing方法得到用户指纹特征的二进制序列,对得到的序列执行一个改进的洗牌算法进行置乱,最后通过Fuzzy Vault方案将特征值与密钥进行绑定。仿真分析表明,利用Fuzzy Vault方案的容错机制和BCH码的纠错机制,该方案可以在保证指纹信息安全的情况下正确恢复密钥。同时,改进的洗牌算法实现了特征模板的可撤销性和不可逆性。     

基于人脸特征和AdaBoost算法的多姿态人脸检测

基于人脸特征和AdaBoost算法,提出一种改进的多姿态人脸检测算法。首先利用肤色特征快速排除绝大部分背景区域,然后在肤色区域中搜索眼睛和嘴巴区域,根据眼睛和嘴巴区域的几何特征所确定的人脸方向分割出大致正向的人脸候选区域,最后利用AdaBoost算法对候选区域进行分类。实验表明,算法能实现多姿态人脸的快速检测,而且对脸部表情和遮挡有较强的鲁棒性。     

基于哈达玛变换和链码角度模板匹配的人脸检测算法

首先利用统计原理检测出一幅图像的肤色区域,再通过哈达玛变换将这些区域从像素域变换到压缩域,最后通过改进和训练链码模板和角度模板来对候选肤色区域进行匹配和检测.实验结果显示,该方法在检测人脸的过程中速度快,漏检率较低,能正确地分辨人脸的肤色、胖瘦,算法设计简单可行,非常适合实时性要求高的图像检索系统.     

Cancellable template generation for speaker recognition based on spectrogram patch selection and deep convolutional neural networks

International Journal of Speech Technology - Nowadays, biometric systems have replaced password-or token-based authentication systems in many fields to improve the security level. However,...     

A new robust video watermarking algorithm based on SURF features and block classification

In this paper, we propose a robust block classification based semi-blind video watermarking algorithm using visual cryptography and SURF (Speed-Up Robust Features) features to enhance the robustness, stability, imperceptibility and real-time performance. A method of selecting the best frames in each shot and the best regions or blocks within best frames is proposed to avoid employing frame–by-frame method for generating owner’s share in order to enhance robustness as well as reducing time complexity. In our method, Owner’s share is generated using the classification of selected robust blocks within the chosen frames along with corresponding watermark information. In extraction process, the SURF features are employed to match the feature points of selected frames with all frames to detect selected frames. Moreover, we resynchronize the embedded regions from distorted video to original sequence using SURF feature points matching. Afterwards, based on these matched feature points, rotation and scaling parameters are estimated next, selected blocks are retrieved using side information being stored eventually, watermark information is reconstructed successfully. Selecting Best frames, best regions, and employing surf features make our method to be highly robust against various kinds of attacks including image processing attacks, geometrical attacks and temporal attacks. Experimental results confirm the superiority of our scheme in case of being applicable in the real world, enhancing robustness and exploiting idea imperceptibility, over previous related methods.     

基于加速鲁棒特征和多示例学习的目标跟踪算法

针对照明变化、形状变化、外观变化和遮挡对目标跟踪的影响,提出一种基于加速鲁棒特征（SURF）和多示例学习（MIL）的目标跟踪算法。首先,提取目标及其周围图像的SURF特征;然后,将SURF描述子引入到MIL中作为正负包中的示例;其次,将提取到的所有SURF特征采用聚类算法实现聚类,建立视觉词汇表;再次,通过计算视觉字在多示例包的重要程度,建立“词-文档”矩阵,并且求出包的潜在语义特征通过潜在语义分析（LSA）;最后,通过包的潜在语义特征训练支持向量机（SVM）,使得MIL问题可以依照有监督学习问题进行解决,进而判断是否为感兴趣目标,最终实现视觉跟踪的目的。通过实验,明确了所提算法对于目标的尺度缩放以及短时局部遮挡的情况都有一定的鲁棒性。     

稳健局部特征非下采样小波域数字水印

目的 基于数字水印技术的音乐作品版权保护是学术界的研究热点之一,多数数字音频水印方案仅仅能够对抗简单的常规信号处理,无法有效抵抗破坏性较强的一般性去同步攻击。为此,提出了一种基于稳健局部特征的非下采样小波域数字水印算法。方法 利用非下采样小波域平滑梯度检测算子从载体音频中提取稳定的音频特征点,结合数字音频样本响应确定局部特征音频段,采用量化调制策略将数字水印信号重复嵌入局部特征音频段中。结果 选取4段典型的采样频率为44.1 kHz、量化精度为16 bit、长度为15 s的单声道数字音频信号作为原始载体进行测试,并与经典算法在不可感知性和鲁棒性两方面进行对比。结果表明,本文算法在含水印音频与原始载体音频间的信噪比平均提升了5.7 dB,同时常规攻击和去同步攻击下的平均检测率分别保持在0.925和0.913,高于大多数传统算法,表明了本文算法具有较好的不可感知性。在常规信号处理（MP3压缩、重新量化、重新采样等）和去同步攻击（幅度缩放、随机剪切、音调伸缩、DA/AD转换、抖动等）方面均具有较好的鲁棒性。结论 本文利用描述能力强且性能稳定的平滑梯度刻画局部数字音频性质,提出一种基于平滑梯度的非下采样小波域音频特征点提取方法,有效解决了音频特征点稳定性差且分布极不均匀的缺点,提高了数字音频水印对音调伸缩、随机剪切、抖动等攻击的抵抗能力。     

基于加速鲁棒特征的非特定目标跟踪算法研究

提出了将加速鲁棒特征SURF与混合匹配法相结合实现对非特定目标的跟踪,跟踪目标既可以是特定目标,亦可在跟踪过程中进行目标切换。首先提取目标图像和待匹配视频的SURF特征点并生成特征向量,然后采用欧氏距离和Hessian矩阵迹相结合确定特征点匹配对,实现目标的定位与跟踪。选用VS 2008平台进行仿真实验,结果表明,该算法既保持了跟踪目标的尺度不变性,又实现了跟踪过程的可控性。     

适于人脸检测的模板匹配快速算法

为提高人脸检测中模板匹配的速度,在积分图像基础上,提出和应用平方积分图像,实现了一种计算速度与图像窗口大小无关的快速灰度均值和方差算法。应用这种快速算法,结合对灰度分布标准化近似计算公式、相关系数和平均偏差计算公式的变换,以及灰度分布标准化处理时省略拷贝图像窗口及窗口灰度值变换等不必要的步骤,大大提高了模板匹配速度。人脸检测实验证明了这种算法的有效性。     

Fusing magnitude and phase features with multiple face models for robust face recognition

High accuracy face recognition is of great importance for a wide variety of real-world applications. Although significant progress has been made in the last decades, fully automatic face recognition systems have not yet approached the goal of surpassing the human vision system, even in controlled conditions. In this paper, we propose an approach for robust face recognition by fusing two complementary features: one is Gabor magnitude of multiple scales and orientations and the other is Fourier phase encoded by spatial pyramid based local phase quantization (SPLPQ). To reduce the high dimensionality of both features, block-wise fisher discriminant analysis (BFDA) is applied and further combined by score-level fusion. Moreover, inspired by the biological cognitive mechanism, multiple face models are exploited to further boost the robustness of the proposed approach. We evaluate the proposed approach on three challenging databases, i.e., FRGC ver2.0, LFW, and CFW-p, that address two face classification scenarios, i.e., verification and identification. Experimental results consistently exhibit the complementarity of the two features and the performance boost gained by the multiple face models. The proposed approach achieved approximately 96% verification rate when FAR was 0.1% on FRGC ver2.0 Exp.4, impressively surpassing all the best known results.     

基于彩色人脸模板的人脸检测算法

针对目前基于色彩的人脸检测只能用于人脸区域的粗检这一不足,提出一种利用人脸的五官位置及色彩信息建立彩色人脸模板的算法。采用光照补偿对图像进行预处理,利用YCbCr空间中的肤色模型进行粗检,确定出人脸候选区域,利用建构好的模板进行搜索比对定位出人脸。实验结果表明该方法对不同光照环境和复杂背景的图片均有较好的适应性,检测精度也得到了提高。     

基于模板匹配的AdaBoost演化算法

提出了基于模板匹配的集成学习AdaBoost演化算法。在该演化算法中,采取训练正反类样本加权模板的方法来构造各个弱学习分类器,克服了常规的基于单一特征构造弱分类器的不足。实验表明,该算法不仅对印刷体字符和部分手写体数字具有较高的识别率,而且减少了分类器构造的训练时间,是稳定、有效的算法。