No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion

This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa.     

Training visual attention in a naturalistic visual environment

The efficiency of training visual attention in the central and peripheral visual field was investigated by means of a visual detection task that was performed in a naturalistic visual environment including numerous, time-varying visual distractors. We investigated the minimum number of repetitions of the training required to obtain the top performance and whether intra-day training improved performance as efficiently as inter-day training. Additionally, our research aimed to find out whether exposure to a demanding task such as a microsurgical intervention may cancel out the effects of training.

Results showed that performance in visual attention peaked within three (for tasks in the central visual field) to seven (for tasks in the periphery) days subsequent to training. Intra-day training had no significant effect on performance. When attention training was administered after exposure to stress, improvement of attentional performance was more pronounced than when training was completed before the exposure. Our findings support the implementation of training in situ at work for more efficient results.

Practitioner Summary: Visual attention is important in an increasing number of workplaces, such as with surveillance, inspection, or driving. This study shows that it is possible to train visual attention efficiently within three to seven days. Because our study was executed in a naturalistic environment, training results are more likely to reflect the effects in the real workplace.     

配加预处理脱硫灰对铁矿烧结基础特性的影响

 半干法脱硫灰堆弃处理占用土地且容易造成二次污染,将脱硫灰预处理后替代CaO熔剂配入烧结有望充分利用其中的熔剂组分,实现脱硫灰在钢铁企业的闭路资源化利用。研究了脱硫灰配加焦粉加热分解特性及替代CaO熔剂配加对铁矿粉烧结基础特性的影响。结果表明,配加1%焦粉可以有效提高脱硫灰分解率,减少CaSO₄的生成。随着预处理脱硫灰替代CaO比例的增加,铁矿粉同化温度和黏结相强度呈现先增加后减小的趋势;液相流动性呈现单调增加趋势,当替代比超过40%时,液相流动性形成了流动性很大的“假象”;黏结相微观结构表明,替代比例小于40%时,有利于烧结试样中铁酸钙的生成;综合考虑,最佳的替代比例应小于40%。     

改性碱式氯化镁晶须/丁苯橡胶复合材料制备与性能研究

以工业活性轻烧氧化镁粉和盐酸为原料,采用水溶液法制备了碱式氯化镁晶须,继而采用硅烷偶联剂对碱式氯化镁晶须进行改性,然后将其与丁苯橡胶混炼得到改性碱式氯化镁晶须/丁苯橡胶复合材料,研究了改性碱式氯化镁晶须对丁苯橡胶力学性能及热学性能的影响。结果表明：采用水溶液法制备得到的碱式氯化镁晶须结构为Mg₂（OH）₃Cl·4H₂O,呈微细纤维状,分布较均匀,长径比大于20;改性碱式氯化镁晶须的加入,可以改善丁苯橡胶的机械强度和阻燃性能。     

碱性添加剂在钛硅分子筛/H2O2催化丙烯环氧化反应中的作用

考察了反应溶液中碱性添加剂{氨水（NH₄OH）、氢氧化钠（NaOH）、碳酸钠（Na₂CO₃）、碳酸铵[(NH₄)₂CO₃]和四甲基氢氧化铵（TMAOH）}及其浓度对钛硅分子筛（TS-1）催化丙烯环氧化反应性能的影响，并采用紫外拉曼光谱（UV-Raman）与气相色谱（GC）联用原位分析（Raman-GC）碱性添加剂的作用机理。结果表明：反应体系中添加碱性添加剂可有效改善TS-1催化丙烯环氧化反应的选择性。不同碱性添加剂对TS-1催化丙烯环氧化活性和稳定性影响不同，NaOH、Na₂CO₃和TMAOH的添加造成催化活性和稳定性降低。NH₄OH或(NH₄)₂CO₃作为添加剂改善环氧化反应选择性的同时提高了反应稳定性，其中以(NH₄)₂CO₃效果最佳。添加(NH₄)₂CO₃浓度为8.0×10^-4mol/L时，TS-1催化丙烯环氧化在固定床反应器上连续运行336h时，X(H₂O₂)仍保持在90%以上。原位Raman-GC分析发现，反应体系中NH₄OH和(NH₄)₂CO₃添加可加快反应活性中间体Ti-OOH(η²)基团的生成，促进反应产物从活性中心快速扩散，从而提高丙烯环氧化反应选择性和稳定性。     

基于深度卷积神经网络的视觉里程计研究

视觉里程计利用视频信息来估计相机运动的位姿参数，实现对智能体的定位。传统视觉里程计方法需要特征提取、特征匹配/跟踪、外点剔除、运动估计、优化等流程，解算非常复杂，因此，提出了基于卷积神经网络的方法来实现端对端的单目视觉里程计。借助卷积神经网络对彩色图片自动学习提取图像帧间变化的全局特征，将用于分类的卷积神经网络转化为帧间时序特征网络，通过三层全连接层输出相机的帧间相对位姿参数。在KITTI数据集上的实验结果表明，提出的Deep-CNN-VO模型可以较准确地估计车辆的运动轨迹，证明了方法的可行性。在简化了复杂模型的基础上，与传统的视觉里程计系统相比，该模型的精度也有所提高。     

乙酰丙酮-目视判读法快速测定白酒中甲醇的含量

目的建立了乙酰丙酮-目视判读法快速测定白酒中甲醇的方法。方法采用乙酰丙酮法,白酒中甲醇经高锰酸钾氧化,草酸还原过量高猛酸钾后,在沸水浴中与乙酰丙酮发生反应,并对分析条件进行了探讨优化,对酒精度影响和干扰因素进行了深入研究并提出了解决办法。结果对优化后的分析条件进行了多个实验室间验证。本快速检验方法灵敏度为100%,特异性为≥94%,假阴性为0%,假阳性率为≤6.0%,相对准确度≥98.5%,满足要求。结论该方法灵敏、准确、快速,适用于白酒中甲醇的含量的现场快速检测。     

舞台灯光对服饰视觉色感的影响研究

在舞台表演中,舞台灯光对人物服饰色彩的视觉体验有很大影响。文章基于光源、布料光谱信息和CIE-1931色度模型,模拟出计算面料色彩推测公式。并选取三种不同色调的LED光源作为舞台灯光,分别对七种面料进行色彩分析,发现深长春花蓝色、中蓝色面料在三种灯光下的色相变化不明显,与太阳光下呈现色彩接近;丁香紫色和兰花紫色面料与灯光色彩倾向一致;金黄色、橙红色和兰花紫色三种颜色在蓝光强烈情况下的色彩视认性更强。最后,结合舞台色彩的视认性和色彩的意象,为舞台服装设计与灯光设计在视觉色感的选择提供帮助。     

基于机器视觉的机车齿轮毂全自动双轴拧紧机的设计和应用

设计了基于机器视觉的机车齿轮毂全自动双轴拧紧机,根据拧紧工艺和扭矩控制原理实现对螺栓拧紧力矩的控制;通过丝杠变径机构,实现不同规格齿轮毂螺栓拧紧;利用机器视觉实现螺栓位置的识别以及初始位置的确定;讨论了自动拧紧机控制系统的硬件组成和软件系统配置,并介绍了防错、防漏功能的设计流程。螺栓自动拧紧机可提高装配精度和操作效率,降低工人的劳动强度。     

主/次显示器视距设计对头部关节舒适度的影响

以视平线可与显示器中心重合为准,分别探讨显示器中心在视平线上方、下方时不同视距对头部关节舒适度的影响. 实验自变量为视距(眼睛与显示器中心的水平距离),因变量为头部关节舒适度. 实验结果显示:1)显示器中心在人视平线上方时,头部舒适性状态始终处于不舒适状态,此时视距与人的头部舒适性关系成正比,即视距越大,头部舒适性越好;2)显示器中心在人视平线下方时,头部关节舒适状态始终处于正常范围,舒适性程度随视距增大而减小.