EFFECTIVE APPEARANCE MODEL FOR PROBABILISTIC OBJECT TRACKING

This paper presents a robust object tracking approach via a spatially constrained colour model. Local image patches of the object and spatial relation between these patches are informative and stable during object tracking. So, we propose to partition an object into patches and develop a Spatially Constrained Colour Model (SCCM) by combining the colour distributions and spatial configuration of these patches. The likelihood of the candidate object is given by estimating the confidences of the pixels in the candidate object region. The appearance model is learnt from the first frame and the tracking is carried out by particle filter. The experimental results show that the proposed tracking approach can accurately track the object with scale changes, pose variance and partial occlusion.

Artificial Neural Network Performing the Forward Operation of Color Appearance Model

A method of the forward operation of color appearance (from colorimetric attributes to color appearance attributes) using an artificial neural network (ANN) is presented The neural network model developed is a multilayer feedforward neural network model for predicting color appearance model (CAM). This method greatly decreased the mathematical computation in color appearance prediction. The error backed-propagation (BP) algorithm was applied in the training of the neural networks, and it was trained and tested by the LUTCHI color appearance datasets which are the most comprehensive one in testing color appearance model. CRT was selected as a typical example in experiment because it is usually used as self-luminous object in fact, and several ways for choosing training samples were included and compared each other. The testing results show that the color appearance prediction using artificial neural network is well consistent with visual evaluation.

Simulation of CIECAM02 color appearance model based on Chinese color system

Color appearance model （CAM） can be used to determine the required colors for repro- duction across changes in cross-media. CIECAM02 color appearance model prediction is implemen- ted by artificial neural networks in this paper, which includes forward and reversed prediction. 1333 color samples as training samples and other 1332 color samples as test samples are selected in the Chinese color system. In order to test the prediction accuracy of neural networks after simulation of CIECAM02 color appearance model, the color-difference formula can be used for the evaluation of forward and reversed models. Results have shown that BP neural-network has acceptable accuracy in simulation of CIECAM02 color appearance model for colors of Chinese color system.

Efficient model building in active appearance model for rotated face

This paper proposes the efficient model building in active appearance model(AAM) for the rotated face.Finding an exact region of the face is generally difficult due to different shapes and viewpoints.Unlike many papers about the fitting method of AAM,this paper treats how images are chosen for fitting of the rotated face in modelling process.To solve this problem,databases of facial rotation and expression are selected and models are built using Procrustes method and principal component analysis(PCA).These models are applied in fitting methods like basic AAM fitting,inverse compositional alignment(ICA),project-out ICA,normalization ICA,robust normalization inverse compositional algorithm(RNIC)and efficient robust normalization algorithm(ERN).RNIC and ERN can fit the rotated face in images efficiently.The efficiency of model building is checked using sequence images made by ourselves.

Facial model fitting algorithm based on active appearance model

Active appearance model(AAM)is an efficient method for the localization of facial feature points,which is also useful for the subsequent work such as face detection and facial expression recognition.In this paper,we mainly discuss the AAMs based on principal component analysis(PCA).We also propose an efficient facial fitting algorithm,which is named inverse compositional image alignment(ICIA),to eliminate a considerable amount of computation resulting from traditional gradient descent fitting algorithm.Finally,3D facial curvature is used to initialize the location of facial feature,which helps select the parameters of initial state for the improved AAM.

The Creative Design Research of Product Appearance Based on Human-machine Interaction and Interface

Today’s product creative design has rendered many fe atures and has brought a great change in our everyday life, there are many new c hallenges in its traditional theory and principle. According to the traditional design theory, the FBS design model pays more attention to the function and stru cture of the product. But this model still couldn’t strengthen the relation bet ween product appearance design and human-machine design effectively. This paper adopt converse design thinking and presents an improved design thinking methodo logy based on C: FBS for product appearance design and give a general summarizat ion for the features, methods and technology based on human-machine interaction and interface. Meanwhile it also combines with the behavior design of product r elated IT fields and constructs a new outline to improve the design of product a ppearance supported by the technology of computer aided design. So the new metho d about design thinking for computer aided design, the new abstract product design model and the key problem of design thinking based on human-machine inte raction and interface are addressed in this paper. This kind of creative design theory that is driven by human-machine interaction and interface will help the development of CAD software system and the research of product design and manufa cture. Additionally, this paper gives some beneficial characters to address the theory based on human-machine interaction and interface. Meanwhile, combining with the developing of computer technology, the trends of design thinking based on t he technology of human-machine interaction and interface are also analyzed and discussed at the end of this paper.

Investigation of Physico-Chemical Characteristics of Stainless Steel Surface and Their Effect on the Appearance Aspects of the Alloy Surface

Stainless steel alloy SS-304 is widely used in many engineering applications primarily for its excellent corrosion resistance, ease of fabrication and aesthetic appeal. Many kitchen appliances are made from SS-304 alloy because of its durability, ease of cleaning and beautiful finish. However, over the years of continuous usage and cleaning by detergent bar and abrasive clothes the initial brightness and shine of the plates and dishes undergo considerable degradation. In this work, we report the results of a thorough investigation of the physico-chemical characteristics of the surface regions of both new and old SS-304 plates of known history of continuous usage to identify the key physical and chemical factors that are responsible for the loss of shine. Several analytical techniques viz. SEM/EDX, AFM, XPS, XRD, Reflectance FTIR, Profilometry and Reflectance spectrometry in the visible region have been used for experimental investigation of surface structure, morphology, roughness profile, chemical composition and appearance measurements of several steel samples. In addition, glossmeter has been used to measure the gloss of the samples at certain specific angles. It seems that surface roughness is one of the key physical parameters that play an important role in the reduction of brightness and shine. The other parameter is the presence of a thin surface film on the steel surface. In order to analyze the experimental data and to predict the shine and brightness phenomena quantitatively, we have used Fresnel’s theory to compute first the reflectance from each component of SS-304 alloy assuming it to be a smooth surface and then extended it to compute the reflectance of the alloy surface (SS-304). In order to interpret the reflectance from old and used plates, we have further used Beckmann’s theory of light scattering from random rough surface to analyze and predict the appearance aspects of the alloy surface quantitatively. Both the experimental and computed results show good agreement, thus validating the reflectance model used for computing the reflectance from SS-304 alloy surface and the appropriateness of Beckmann’s model of random rough surface.

Non-invasive optical characterization and estimation of Zn porosity in gas tungsten arc welding of Fe–Al joints using CR model and OES measurements

In this study,we employed a non-invasive approach based on the collisional radiative(CR)model and optical emission spectroscopy(OES)measurements for the characterization of gas tungsten arc welding(GTAW)discharge and quantification of Zn-induced porosity during the GTAW process of Fe–Al joints.The OES measurements were recorded as a function of weld current,welding speed,and input waveform.The OES measurements revealed significant line emissions from Zn-I in 460–640 nm and Ar-I in 680–800 nm wavelength ranges in all experimental settings.The OES coupled CR model approach for Zn-I line emission enabled the simultaneous determination of both essential discharge parameters i.e.electron temperature and electron density.Further,these predictions were used to estimate the Zn-induced porosity using OES-actinometry on Zn-I emission lines using Ar as actinometer gas.The OES-actinometry results were in good agreement with porosity data derived from an independent approach,i.e.x-ray radiography images.The current study shows that OES-based techniques can provide an efficient route for real-time monitoring of weld quality and estimate porosity during the GTAW process of dissimilar metal joints.

3D fluid model analysis on the generation of negative hydrogen ions for negative ion source of NBI

A radio-frequency(RF) inductively coupled negative hydrogen ion source(NHIS) has been adopted in the China Fusion Engineering Test Reactor(CFETR) to generate negative hydrogen ions.By incorporating the level-lumping method into a three-dimensional fluid model,the volume production and transportation of H^(-) in the NHIS,which consists of a cylindrical driver region and a rectangular expansion chamber,are investigated self-consistently at a large input power(40 k W) and different pressures(0.3–2.0 Pa).The results indicate that with the increase of pressure,the H^(-) density at the bottom of the expansion region first increases and then decreases.In addition,the effect of the magnetic filter is examined.It is noteworthy that a significant increase in the H^(-) density is observed when the magnetic filter is introduced.As the permanent magnets move towards the driver region,the H^(-) density decreases monotonically and the asymmetry is enhanced.This study contributes to the understanding of H-distribution under various conditions and facilitates the optimization of volume production of negative hydrogen ions in the NHIS.

芙蓉李果实成熟期间的综合品质评价指标筛选与表观预测模型构建

目的科学评价芙蓉李果实成熟期间的营养品质,建立色度值表观特征与营养品质的关系。方法以福建省主栽品种芙蓉李为研究对象,对其成熟期间果糖、葡萄糖、蔗糖、苹果酸、奎尼酸、琥珀酸、柠檬酸、富马酸、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷、多酚、黄酮、类胡萝卜素等13个品质指标进行分析和综合评价。结果芙蓉李成熟期间,各品质指标的含量变化存在显著差异(P<0.05),综合运用相关分析、因子分析、绝对因子分析-多元线性回归(absolute principal component scores-multiple linear regression,APCS-MLR)分析筛选可反映芙蓉李综合品质的主要指标。因子分析提取出3个主因子,贡献率分别为52.677%、23.468%、11.649%,累计贡献率为87.794%。综合APCS-MLR等数理统计分析,主因子1主要对果糖、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷贡献较大,贡献率分别为53.00%、73.85%、55.54%;主因子2主要对蔗糖、富马酸、果糖、柠檬酸的贡献率较大,分别为28.26%、18.70%、16.14%、15.59%;主因子3主要对多酚(29.13%)和黄酮(28.28%)有较大贡献率;选取3个主因子总贡献率高于60%的果糖、葡萄糖、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷作为综合品质评价的主要指标。分别对已筛选出的4个主要评价指标与色度值进行多元线性逐步回归分析,建立4个主要指标与色度值的表观预测模型,各模型均具有较好的拟合度,预测值与实测值的均方根误差较小;进一步验证结果表明,通过色度值对4个指标的预测具有较高的可靠性和准确性。结论本研究筛选出的主要指标及预测模型可更加简单、便捷地评价芙蓉李果实成熟期间的综合品质。

缺血缺氧脑瘫大鼠的时效研究

目的:基于缺血缺氧脑瘫大鼠神经功能评分(Zea-Longa评分)、脑组织肉眼观和大脑海马区胱天蛋白酶-9(Caspase-9)、胱天蛋白酶-3(Caspase-3)的表达水平变化,探讨缺血缺氧模型脑瘫大鼠的有效时长。方法:选取3周龄斯泼累格·多雷(SD)健康大鼠,随机分为正常组和模型组,采用改良的Rice-Vannucci方法建立脑瘫模型,造模后第1、7、14、21天,观察各组大鼠的一般情况并进行神经功能评分,在第7、14、21天分批处死大鼠并取脑组织,观察各组大鼠左侧脑组织,检测海马区Caspase-9、Caspase-3的表达水平。结果:一般情况:造模后第1天,与正常组比较,模型组大鼠左侧瞳孔缩小、姿势异常、自发或夹尾左旋、自主活动减少、兴奋性降低、肌肉颤动、头颤,抽搐,抓取时抵抗反应明显,随着时间延长,以上异常行为逐渐消失,造模后21 d基本消失不见,但左侧瞳孔一直小于对侧;Zea-Longa评分:与正常组比较,模型组造模后7、14 d Zea-Longa评分较高,差异有统计学意义(P<0.05);脑组织肉眼观:与正常组比较,模型组造模后7、14及21 d大鼠左侧脑组织有不同程度的萎缩和坏死;免疫组化结果:与正常组比较,模型组造模后7 d、14 d Caspase-9、Caspase-3的表达水平均显著升高,差异有统计学意义(P<0.05)。结论:3周龄缺血缺氧脑瘫模型大鼠的有效时长为14~21 d,可干预14 d。

农机产品设计中艺术外观表达效果研究

为了提高农机外观造型效果,将艺术外观美学设计引入到农机产品的设计中,并采用SolidWorks软件设计了农用拖拉机的三维模型,利用软件提供的工具对模型进行了渲染和装饰,实现了三维外观造型和艺术效果。以农用拖拉机发动机引擎盖为例,通过分析其曲面建模步骤实现了引擎盖的设计,最后利用SolidWorks进行了整机的虚拟装配试验。结果表明:将艺术外观表达效果应用在农用拖拉机设计中,改善了产品的造型和外观效果,大幅提升了欣赏性。

涤纶混纺面料抽褶裙褶皱造型评价与分析

针对抽褶裙的抽褶造型效果问题,文章以半身裙为研究对象,选取7种涤纶混纺织物进行保形性能、力学性能测试和主观评价试验,筛选出3种较适宜抽褶的面料,分别为涤麻混纺(70:30)、涤棉混纺(50:50)、竹黏纤维与涤纶混纺(50:50)面料,并分别制作3组相同尺寸的样裙,每组包含5cm和10cm抽褶长度,对3组抽褶裙进行Kendall'sW检验主观评价试验。研究得出:竹黏纤维与涤纶混纺(50:50)面料(抽褶长度10cm)美观度评价最好;织物密度、线密度、厚度与织物折皱回复性、力学性能呈正相关,若织物折皱回复性、抗拉伸性越好,则织物呈刚性,折皱效果立体生硬,可改变混纺成分提升抽褶裙造型美观度。

明挖隧道清水混凝土模型试验研究与实践应用

清水混凝土不需要进行任何的外部装饰,近年来备受建筑行业的关注。文章开展清水混凝土水桶试验、混凝土缩尺模型试验研究,优选原材料,确定骨料级配,精确设计混凝土外加剂,优化清水混凝土配合比,制备满足明挖隧道结构力学、抗裂与耐久性能的清水混凝土;采用定性与定量评价相结合的方式,研究了模板、脱模剂以及浇筑振捣等对清水混凝土外观质量的影响规律,明确了适用于明挖隧道清水混凝土的技术参数,并在江阴靖江长江隧道成功实践应用,取得了较好的效果,具有广泛的应用前景和工程借鉴意义。

室内外气压平衡装置过风管施工技术

以某办公楼为例,对室内外气压平衡装置过风管施工技术进行研究,综述了通过在门顶设置室内外气压平衡装置(过风管道、孔口百叶、管道内隔音装置),消除门启闭时所产生空气正负压,使室内外气压保持平衡,并通过管内粘贴玻纤毡复合玻璃棉板和设置橡皮阀,以消除风管运行产生的噪音,减少风管壁的冷能量损失,并起到隔音效果。

Machine learning prediction model for gray-level co-occurrence matrix features of synchronous liver metastasis in colorectal cancer

BACKGROUND Synchronous liver metastasis(SLM)is a significant contributor to morbidity in colorectal cancer(CRC).There are no effective predictive device integration algorithms to predict adverse SLM events during the diagnosis of CRC.AIM To explore the risk factors for SLM in CRC and construct a visual prediction model based on gray-level co-occurrence matrix(GLCM)features collected from magnetic resonance imaging(MRI).METHODS Our study retrospectively enrolled 392 patients with CRC from Yichang Central People’s Hospital from January 2015 to May 2023.Patients were randomly divided into a training and validation group(3:7).The clinical parameters and GLCM features extracted from MRI were included as candidate variables.The prediction model was constructed using a generalized linear regression model,random forest model(RFM),and artificial neural network model.Receiver operating characteristic curves and decision curves were used to evaluate the prediction model.RESULTS Among the 392 patients,48 had SLM(12.24%).We obtained fourteen GLCM imaging data for variable screening of SLM prediction models.Inverse difference,mean sum,sum entropy,sum variance,sum of squares,energy,and difference variance were listed as candidate variables,and the prediction efficiency(area under the curve)of the subsequent RFM in the training set and internal validation set was 0.917[95%confidence interval(95%CI):0.866-0.968]and 0.09(95%CI:0.858-0.960),respectively.CONCLUSION A predictive model combining GLCM image features with machine learning can predict SLM in CRC.This model can assist clinicians in making timely and personalized clinical decisions.

基于FBS扩展模型的适老化产品易用性设计研究

目的 为改进适老化产品易用性问题,提出一种融合需求分析和外观编码的产品概念设计扩展模型。方法 首先运用文献分析法了解适老化产品易用性设计研究和经典概念设计模型的发展现状,同时结合产品语义学中外观具备的传达产品功能和操作方式的价值,提出将产品外观编码应用于改进适老化产品易用性的新思路。其次对传统FBS模型进行扩展,构建一个包含“需求–功能–行为–结构–外观”多种要素的概念设计扩展模型。以需求分析和外观编码为重点,具体阐述模型推导过程。进而通过老年用户判断产品功能和操作方式的正确概率和反应时间量化产品易用性,从而优选出最佳的适老化产品设计方案。最后在设计应用中,以家用电动护理床智能遥控的易用性改进设计为例,验证了NFBSA模型的可行性。结论 NFBSA模型能有效改进产品易用性,有助于缩小老年用户与适老化产品之间的使用鸿沟,进一步增强老年用户对新兴产品的信心,同时给予设计师与相关产品的易用性设计研究以参考价值。

基于YOLO模型的小麦外观分类算法研究

小麦种植广泛且营养丰富,其品质问题需要重点关注。小麦品质的衡量指标主要是不完善粒占比。为此,需要对小麦颗粒进行分类识别。提出了1种基于你只看一次(YOLO)模型的小麦外观自动分类算法,创新性地将YOLO模型应用于小麦外观分类场景。对采集得到的小麦样本图像切割、筛选、扩充和标记,构建了完善粒与不完善粒图像库。对YOLO网络进行了训练,利用训练后的模型对麦粒图像进行了测试,实现了完善粒、不完善粒分别为91.7%、87.1%的分类准确率。这种自动分拣麦粒的检验方法避免了人工视觉疲劳后的误判,而且检测效率显著提高,为小麦外观分类研究提供了新的思路。

机器视觉的烟叶物理特性表征方法

为了研究梅州地区各等级烟叶的外观特征与物理特性间的关系,找到一种通过烟叶外观特征表征其物理特性的方法,选取了梅州6个产地、12个等级的初烤烟叶共977片。使用机器视觉设备和质构仪分别检测了烟叶样本的外观特征和物理特性。选取其中781片烟叶样本作为训练集,使用了弹性网络、极端随机树、支持向量机等回归模型以及模型融合技术分别构建了基于烟叶外观特征的最大拉力、剪切力和撕裂度的表征模型。选取196片烟叶样本作为测试集,以平均绝对误差为模型评价指标,评估了3种表征模型的泛化性能。结果表明,对于最大拉力的表征模型而言,模型在测试集上的预测值与真实值的相关系数超过0.73,拟合优度为0.54;对于剪切力的表征模型而言,模型在测试集上的预测值与真实值的相关系数超过0.78,拟合优度为0.60;对于撕裂度的表征模型而言,模型在测试集上的预测值与真实值的相关系数超过0.75,拟合优度为0.56。烟叶的外观特征对于烟叶的最大拉力、剪切力和撕裂度具有一定的表征能力。