复杂场景实时目标检测方法

针对含有非平稳背景的复杂场景,提出一种基于空间混合高斯模型的实时目标检测方法.该方法以混合高斯模型作为颜色分布的统计框架,并在空间邻域中利用背景与前景隶属度之间的竞争确定像素的归属,提高了检测准确率;同时通过基于偏差均值的匹配判断和低权重模型的移除提升了混合高斯统计框架的性能,以实时地对运动目标进行准确的检测.实验结果表明,文中方法对非平稳背景有很好的适应能力,在检测准确率和运行效率上均优于其他检测方法.     

黏-砂混合土压缩特性与微观结构特征关系研究

黏-砂混合土在吹填土地基中广泛应用,混合土地基变形与微观结构息息相关。为探讨黏-砂混合土压缩变形的微观机制,以黏土与砂不同配比的混合土为研究对象,利用压缩、扫描电镜(SEM)试验和图像处理技术(IPP)对固结前后试样的颗粒排列、孔隙分布进行定性和定量分析,从微观层面探讨了混合土微观结构随固结压力变化的演变机制。结果表明:随着含砂量的增大,混合土孔隙比呈先减小后增大的趋势,压缩系数不断减小;大、中孔隙随着含砂量增大明显增多,颗粒间接触方式从以边-面、面-面接触为主向点-点、点-面接触过渡;固结作用提高了颗粒排列的密实性和有序性,孔径分布向小孔径范围移动,大孔隙面积占比最大降幅达31.39%,中孔隙面积显著增加,对微、小孔隙影响不明显;土体颗粒的定向概率熵与和含砂量呈正线性相关,与压缩系数a_1-2呈负线性相关,含砂量越大,混合土颗粒排列越混乱,定向概率熵越大,其压缩性越低。由此可见,固结压力和配比不同引起的颗粒、孔隙微观结构参数变化是导致混合土压缩特性差异的内在原因。     

Improving human robot collaboration through Force/Torque based learning for object manipulation

Human–Robot Collaboration (HRC) is a term used to describe tasks in which robots and humans work together to achieve a goal. Unlike traditional industrial robots, collaborative robots need to be adaptive; able to alter their approach to better suit the situation and the needs of the human partner. As traditional programming techniques can struggle with the complexity required, an emerging approach is to learn a skill by observing human demonstration and imitating the motions; commonly known as Learning from Demonstration (LfD). In this work, we present a LfD methodology that combines an ensemble machine learning algorithm (i.e. Random Forest (RF)) with stochastic regression, using haptic information captured from human demonstration. The capabilities of the proposed method are evaluated using two collaborative tasks; co-manipulation of an object (where the human provides the guidance but the robot handles the objects weight) and collaborative assembly of simple interlocking parts. The proposed method is shown to be capable of imitation learning; interpreting human actions and producing equivalent robot motion across a diverse range of initial and final conditions. After verifying that ensemble machine learning can be utilised for real robotics problems, we propose a further extension utilising Weighted Random Forest (WRF) that attaches weights to each tree based on its performance. It is then shown that the WRF approach outperforms RF in HRC tasks.     

混合高斯模型结合五帧差分的运动目标检测

在复杂背景下,光照变化、目标短暂遮挡以及背景运动等因素会导致运动目标检测精度较低.提出一种结合改进混合高斯模型和改进五帧差分的运动目标检测算法,首先在混合高斯模型中加入自适应学习率以及背景学习速率更新策略有效解决传统背景更新速率恒定而出现的残影现象;然后利用改进的五帧差分法克服运动目标短暂遮挡问题,并加入光照阈值判别因素,有效减弱光照变化带来的影响;最后对两者结果进行或运算进而得到最终检测结果.实验结果表明,该融合算法在复杂环境下具有一定的抗干扰能力,运动目标检测精度较高.     

Comparing ANN and GMM in a voice conversion framework

In this paper, we present a comparative analysis of artificial neural networks (ANNs) and Gaussian mixture models (GMMs) for design of voice conversion system using line spectral frequencies (LSFs) as feature vectors. Both the ANN and GMM based models are explored to capture nonlinear mapping functions for modifying the vocal tract characteristics of a source speaker according to a desired target speaker. The LSFs are used to represent the vocal tract transfer function of a particular speaker. Mapping of the intonation patterns (pitch contour) is carried out using a codebook based model at segmental level. The energy profile of the signal is modified using a fixed scaling factor defined between the source and target speakers at the segmental level. Two different methods for residual modification such as residual copying and residual selection methods are used to generate the target residual signal. The performance of ANN and GMM based voice conversion (VC) system are conducted using subjective and objective measures. The results indicate that the proposed ANN-based model using LSFs feature set may be used as an alternative to state-of-the-art GMM-based models used to design a voice conversion system.     

基于品质函数估计的非线性盲源分离算法

研究非线性盲源信号分离优化问题。由于混合信号同时包含超高斯和亚高斯信号且混合信号具有很强的非线性时,传统的非线性盲源分离算法中对于品质函数的选取一般都是通过经验,现有算法难以取得理想的分离效果。在Pearson模型的基础上提出了一种新的估计品质函数的方法,算法能够成功地估计出次高斯(sub-Gaussian)和超高斯(super-Gaussi-an)混合信号的品质函数,同时克服了Pearson模型对同类信号只能估计得到相同的品质函数的缺陷,提高了算法的估计精度。通过在MATLAB仿真验证了算法的可行性和有效性,成功估计出源信号的品质函数且实现了非线性盲源分离。     

Preparation of β-cyclodextrin/SBS modified asphalts for the improvement of anti-aging,rheological property,and storage stability

Styrene-butadiene-styrene (SBS) modified asphalt (SMA) has been widely used in road engineering for decade. However, the phase separation of SMA was obvious during the transport and SBS degraded after aging. To resolve these problems, β-cyclodextrin (β-CD) was used to modify SMA in this work. Conventional properties, storage stability, the effect of short-term aging on the morphology, and rheological property for SMA and β-CD/SMA were investigated. The softening point of modified asphalt reached to the maximum of 66.7°C when 1 wt% β-CD was added to SMA, where the penetration had shown the minimum of 80.8 dmm. In addition, the ductility of β-CD/SMA increased to the maximum of 797 mm when the content of β-CD was increased to 5 wt%. Furthermore, incorporation of β-CD improved the storage stability of SMA. Importantly, the aggregation of SBS was observed in β-CD/SMA, but modifiers distributed uniformly after a short-term aging. The rutting resistance and antiaging performances of SMA were also improved by the addition of β-CD. Considering the comprehensive properties of modified asphalt, the optimum content of β-CD was found to be 2 wt%.     

高温高湿盐环境下SBS改性沥青胶浆的高温性能

基于自行设计的室内盐蚀干湿循环试验,采用动态剪切流变仪,对SBS改性沥青胶浆进行温度扫描试验和多重应力重复蠕变恢复(MSCR)试验. 以3.2 kPa应力下的不可恢复蠕变柔量J_nr,3.2为胶浆高温流变性能评价指标,分析试验环境和干湿循环耦合作用对胶浆流变性能的影响. 采用灰色关联理论,探究J_nr,3.2与常规流变参数、干湿循环次数及试验环境之间的关联性. 结果表明,随着盐蚀干湿循环次数的增加,胶浆的复数切变模量、车辙因子及J_nr,3.2均呈增大趋势,相位角和蠕变恢复率呈减小趋势. 在同种试验条件下,硫酸盐环境对胶浆高温性能的影响最大. J_nr,3.2与改进型车辙因子、试验环境的灰色关联度最大,关联度系数均大于0.93. 建议采用日常清扫、定期洒水冲洗的方式来减小路面盐分的积累,提高高温高湿环境中沥青路面的抵抗变形的能力.     

食品用洗涤剂中甲基异噻唑啉酮类防腐剂检测的必要性

甲基异噻唑啉酮类防腐剂是一类具有高效、广谱的杀菌和抑菌性能的防腐剂,广泛应用于各类防腐领域,但该类防腐剂能否用于食品相关产品还有待研究。文章主要介绍了甲基氯异噻唑啉酮与甲基异噻唑啉酮的混合物和甲基异噻唑啉酮两类防腐剂,以及近年各国对化妆品中甲基异噻唑啉酮类防腐剂的限量要求。从调查数据看,市场上大多食品用洗涤剂都含有甲基异噻唑啉酮类防腐剂,有的含量甚至超过化妆品安全技术规范中最大允许浓度,对人体健康可能会产生较大威胁。因此,有必要对食品用洗涤剂中甲基异噻唑啉酮类防腐剂进行检测,并建议在食品用洗涤剂国家标准中列入对甲基异噻唑啉酮类防腐剂的限量。