自适应特征融合的相关滤波跟踪算法

为提高复杂背景下目标跟踪的鲁棒性,提出一种基于相关滤波的自适应特征融合目标跟踪算法.在HOG特征基础上,增加HSV颜色概率直方图,以此获得准确的位置预测.然后分别训练颜色名和HOG特征,并根据两个响应图的峰值自适应地分配融合系数,进而基于尺度池方法,采用多通道特征实现目标的尺度估计.模型的高置信度更新由两个响应图的平均...     

基于差异颜色特性的自适应互补学习目标跟踪

针对模板与像素互补学习(Staple)算法中梯度直方图(HOG)特征对目标形状与尺度变化表达能力较弱,以及不能自适应地进行模型融合与模型更新的问题,提出一种基于差异颜色特性的自适应互补学习目标跟踪算法.首先在HOG特征基础上,增加具有良好形状与尺度不变性的颜色名特征,使用此多通道特征计算位置滤波器的响应图;其次计算颜色直方图特征的特征响应图,依据2种响应图的峰值和平均峰相关能量(APCE)指标自适应地分配权重,得到最终融合响应图;最后根据融合响应图的峰值和APCE指标实现高置信度的模型更新.在OTB-13和OTB-15标准测试集上与5种主流的跟踪算法进行实验的结果表明,该算法在目标形变、尺度变化、光照变化、遮挡等情况下均具有较高的鲁棒性,其跟踪精度和成功率指标都优于Staple及其他主流的跟踪算法.     

多特征分层融合的相关滤波鲁棒跟踪

目的 为提高目标跟踪的鲁棒性,针对相关滤波跟踪中的多特征融合问题,提出了一种多特征分层融合的相关滤波鲁棒跟踪算法。方法 采用多通道相关滤波跟踪算法进行目标跟踪时,从目标和周围背景区域分别提取HOG（histogram of oriented gradient）、CN（color names）和颜色直方图3种特征。提出的分层融合算法首先采用自适应加权融合策略进行HOG和CN特征的特征响应图融合,通过计算特征响应图的平滑约束性和峰值旁瓣比两个指标得到融合权重。将该层融合结果与基于颜色直方图特征获得的特征响应图进行第2层融合时,采用固定系数融合策略进行特征响应图的融合。最后基于融合后的响应图估计目标的位置,并采用尺度估计算法估计得到目标更准确的包围盒。结果 采用OTB-2013（object tracking benchmark 2013）和VOT-2014（visual object tracking 2014）公开测试集验证所提跟踪算法的性能,在对多特征分层融合参数进行分析的基础上,与5种主流基于相关滤波的目标跟踪算法进行了对比分析。实验结果表明,本文算法的目标跟踪精度有所提高,其跟踪精度典型值比Staple算法提高了5.9%（0.840 vs 0.781）,同时由于有效地融合了3种特征,在多种场景下目标跟踪的鲁棒性优于其他算法。结论 提出的多特征分层融合跟踪算法在保证跟踪准确率的前提下,跟踪鲁棒性优于其他算法。当相关滤波跟踪算法采用了多个不同类型特征时,本文提出的分层融合策略具有一定的借鉴性。     

基于深度估计和特征融合的尺度自适应目标跟踪算法

针对核相关滤波目标跟踪算法(KCF)使用单特征来描述所跟踪的目标,在复杂环境下,目标尺 度发生较大变化时,无法准确跟踪目标的问题,提出基于深度估计和特征融合的尺度自适应目标跟踪算法。首 先利用深度神经网络估计视频序列中目标的深度,建立并训练深度-尺度估计模型;在跟踪过程中,融合目标 方向梯度直方图(HOG)特征和 CN (Color Name)特征训练相关滤波器,利用深度估计网络得到目标深度值,并 利用深度-尺度估计模型得到目标的尺度值,从而在目标尺度发生变化时,能够调整目标框大小,实现尺度自 适应的目标跟踪算法。实验结果表明,与经典的 KCF 算法相比,可获得更高的精度,与尺度自适应的判别型 尺度空间跟踪(DSST)算法相比,在尺度变化较大时,跟踪速度更快;在环境复杂、目标被遮挡时,鲁棒性更好。     

基于上下文感知与自适应响应融合的相关滤波跟踪算法

针对当前相关滤波跟踪算法在抗背景干扰、响应融合方式以及模型更新策略上的不足,提出一种基于上下文感知与自适应响应融合的相关滤波跟踪算法.通过引入上下文感知技术,提高算法在背景杂波及遮挡等跟踪场景下的鲁棒性;通过研究HOG特征和颜色直方图特征二者响应图和响应值的特点,提出一种自适应响应融合方法,提升融合响应图的可靠性;在模型更新方面,采用了高置信度模型更新策略来减轻传统模型更新策略中模型污染及跟踪漂移的问题.实验结果表明,本文算法在OTB50数据集上达到了74.7%的跟踪精度,跟踪成功率为54.8%,均优于对比的主流相关滤波跟踪算法,并且在背景杂波、光照变化、遮挡、运动模糊等复杂跟踪场景中具有较好的跟踪精度与鲁棒性.     

自适应多特征融合相关滤波目标跟踪

目的 针对现实场景中跟踪目标背景复杂、光照变化、快速运动、旋转等问题,提出自适应多特征融合的相关滤波跟踪算法。方法 提取目标的HOG（histogram of oriented gradients）特征和利用卷积神经网络提取高、低层卷积特征,借助一种自适应阈值分割方法评估每种特征的有效性,得到特征融合的权重比。根据权重系数融合每种特征的响应图,并据此得到目标的新估计位置,利用尺度相关滤波器计算目标尺度,得到目标尺度完成跟踪。结果 在OTB（object tracking benchmark）-2013公开数据集上进行实验,在对多特征融合进行分析的基础上,测试了本文算法在11种不同属性下的跟踪性能,并与当前流行的7种算法进行对比分析。结果表明,本文算法的成功率和精确度均排名第1,相较于基准算法DSST （discriminative scale space tracking）跟踪精确度提高了4%,成功率提高了6%。在复杂场景下比其他主流算法更具有鲁棒性。结论 本文算法以DSST相关滤波跟踪器为基准算法,借助自适应阈值分割方法评估每种特征的有效性,自适应融合两层卷积特征和HOG特征,使得判别性越强的单一特征融合权重越大,较好表达了目标的外观模型,在背景复杂、目标消失、光照变化、快速运动、旋转等场景下表现出较强的跟踪准确性。     

基于多特征和尺度估计的KCF_MTSA算法

多模板尺度自适应核相关滤波器（KCF_MTSA）跟踪算法在目标移动模糊、旋转和尺度变化时跟踪距离精度与成功率较低。针对该问题,提出一种结合多特征和尺度估计的改进KCF_MTSA目标跟踪算法。采用方向梯度直方图和颜色名两种特征对目标进行表征,在训练阶段分别使用多模板核相关滤波器对上述特征进行训练,同时在检测阶段将两个滤波器的响应以权重形式进行自适应融合获取响应图实现目标定位,并使用一维相关滤波器进行目标尺度估计。实验结果表明,该算法的跟踪距离精度和准确率较改进前KCF_MTSA算法有明显提升,其距离精度和准确率分别提高15.8%和28.5%。     

特征融合与重定位卷积算子跟踪算法研究

针对卷积操作目标跟踪算法(ECO-HC)在遮挡、背景等干扰问题导致跟踪精度下降的问题,提出了一种自适应特征融合的卷积相关滤波算法,将CN与HOG特征进行加权融合,通过计算各自的响应来确定各自特征在下一帧的权重,将特征各自的优势充分发挥出来.此外,针对目标跟踪失败问题,提出利用形变相似多样性原理,构建目标重定位模块,当出现遮挡、快速移动等复杂情况造成跟踪的可靠性降低时,综合考虑目标响应得分、空间权重得分和形变相似多样性得分来确定目标的最终位置,实现重定位.实验证明,改进后算法与ECO-HC相比,针对目标遮挡、背景干扰等复杂情况,有效地提高了跟踪精度,鲁棒性更强.     

基于双模型融合的自适应目标跟踪算法

针对目标跟踪过程中的光照变化、背景混乱和目标形变等问题,提出一种背景抑制的HS直方图和核相关滤波双模型融合的自适应跟踪算法。首先引入非线性核相关滤波跟踪模型;其次提出背景抑制的HS颜色直方图跟踪模型,通过分离亮度分量以减小光照干扰,并采用背景加权突出目标信息;然后提出一种自适应融合策略,根据目标与背景的HS特征相似度来动态调整两个模型融合权重,以降低背景混乱和目标姿态变化的影响;最后针对目标尺度变化问题,采用尺度金字塔估计策略进行解决。实验表明,与现有算法相比,提出的算法能更好降低光照、背景混乱等复杂因素干扰,鲁棒性更强。     

响应置信度的多特征融合核相关滤波跟踪算法

摘要：针对传统核相关滤波（KCF）在跟踪彩色视频序列不能有效利用颜色特征,并且处理目标遮挡和形变能力低等问题,提出一种响应置信度的多特征融合核相关滤波跟踪算法。该算法首先提取目标图像的方向直方图特征和颜色直方图特征,通过计算高响应值点在响应图上层的占比,来判断目标的跟踪情况,进而调整学习率的大小;然后用两种特征的平均峰相关能量(APCE)和最大响应峰值的乘积来加权融合目标位置。实验对比表明,提出的跟踪算法在精度和成功率上相对于KCF算法分别提升了12.8%和22.6%, 在目标发生遮挡、快速移动、旋转等复杂情况下仍然具有较强的鲁棒性。     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.     

Editorial: Special issue on recent advances in hybrid control theory and applications

正The demands of a rapidly advancing technology for faster and more accurate controllers have always had a strong influence on the progress of automatic control theory.In recent years control problems have been arising with increasing frequency in widely different areas,which cannot be addressed using conventional control techniques.The principal reason for this is the fact that a highly competitive economy is forcing systems to operate in regimes where     

Information for Authors

正Aim The Journals of Zhejiang University-SCIENCE(A/B/C)areedited by the international board of distinguished Chinese andforeign scientists,and are aimed to present the latest devel-opments and achievements in scientific research in China andoverseas to the world’s scientific circles,especially to stimulateand promote academic exchange between Chinese and for-eign scientists everywhere.     

Enhancing a leaf radiative transfer model to estimate concentrations and in vivo specific absorption coefficients of total carotenoids and chlorophylls a and b from single-needle reflectance and transmittance

The relative concentrations of different pigments within a leaf have significant physiological and spectral consequences. Photosynthesis, light use efficiency, mass and energy exchange, and stress response are dependent on relationships among an ensemble of pigments. This ensemble also determines the visible characteristics of a leaf, which can be measured remotely and used to quantify leaf biochemistry and structure. But current remote sensing approaches are limited in their ability to resolve individual pigments. This paper focuses on the incorporation of three pigments—chlorophyll a, chlorophyll b, and total carotenoids—into the LIBERTY leaf radiative transfer model to better understand relationships between leaf biochemical, biophysical, and spectral properties.Pinus ponderosa and Pinus jeffreyi needles were collected from three sites in the California Sierra Nevada. Hemispheric single-leaf visible reflectance and transmittance and concentrations of chlorophylls a and b and total carotenoids of fresh needles were measured. These data were input to the enhanced LIBERTY model to estimate optical and biochemical properties of pine needles. The enhanced model successfully estimated reflectance (RMSE = 0.0255, BIAS = 0.00477, RMS%E = 16.7%), had variable success estimating transmittance (RMSE = 0.0442, BIAS = 0.0294, RMS%E = 181%), and generated very good estimates of carotenoid concentrations (RMSE = 2.48 µg/cm², BIAS = 0.143 µg/cm², RMS%E = 20.4%), good estimates of chlorophyll a concentrations (RMSE = 10.7 µg/cm², BIAS = − 0.992 µg/cm², RMS%E = 21.1%), and fair estimates of chlorophyll b concentrations (RMSE = 7.49 µg/cm², BIAS = − 2.12 µg/cm², RMS%E = 43.7%). Overall root mean squared errors of reflectance, transmittance, and pigment concentration estimates were lower for the three-pigment model than for the single-pigment model. The algorithm to estimate three in vivo specific absorption coefficients is robust, although estimated values are distorted by inconsistencies in model biophysics. The capacity to invert the model from single-leaf reflectance and transmittance was added to the model so it could be coupled with vegetation canopy models to estimate canopy biochemistry from remotely sensed data.     

Mr. Twinn’s bombes

This article discusses the history and design of the special versions of the bombe key-finding machines used by Britain’s Government Code & Cypher School (GC&CS) during World War II to attack the Enigma traffic of the Abwehr (the German military intelligence service). These special bombes were based on the design of their more numerous counterparts used against the traffic of the German armed services, but differed from them in important ways that highlight the adaptability of the British bombe design, and the power and flexibility of the diagonal board. Also discussed are the changes in the Abwehr indicating system that drove the development of these machines, the ingenious ways in which they were used, and some related developments involving the bombes used by the U.S. Navy’s cryptanalytic unit (OP-20-G).