数控加工三维场景几何建模技术研究

讨论了基于构件技术的数控加工三维场景建模技术,并以OpenGL和Visual C++6.0为开发平台,开发出一个基于STL文件格式的建模系统.     

Blind omnidirectional image quality assessment with representative features and viewport oriented statistical features

With the development of information technologies, various types of streaming images are generated, such as videos, graphics, Virtual Reality (VR)/omnidirectional images (OIs), etc. Among them, the OIs usually have a broader view and a higher resolution, which provides human an immersive visual experience in a head-mounted display. However, the current image quality assessment works cannot achieve good performance without considering representative human visual features and visual viewing characteristics of OIs, which limited OIs’ further development. Motivated by the above problem, this work proposes a blind omnidirectional image quality assessment (BOIQA) model based on representative features and viewport oriented statistical features. Specifically, we apply the local binary pattern operator to encoder the cross-channel color information, and apply the weighted LBP to extract the structural features. Then the local natural scene statistics (NSS) features are extracted by using the viewport sampling to boost the performance. Finally, we apply support vector regression to predict the OIs’ quality score, and experimental results on CVIQD2018 and OIQA2018 Databases prove that the proposed model achieves better performance than state-of-the-art OIQA models.     

设计语用学的范式研究

目的确定设计语用学研究范畴,建立设计语用学的研究范式,进而通过设计语用学理论发展对设计方法论提供新的理论依据。方法从设计符号传播语境视角出发,对设计方、用户和用户的社交对象之间的设计符号传播模式进行论述。结论结合整合营销传播理论和设计事理学理论,得出了设计语用学的研究范畴、研究意义、研究核心及整合产品设计营销传播与定义设计符号使用场景两种设计语用学的研究路径,完成了设计语用学的理论框架。     

民营书商参与高校图书现采工作探析

从民营书商参与图书现采的背景出发,分析了民营书商参与图书现采的优缺点,并对其未来的发展趋势提出了看法。     

The Skeptical Explorer: A Multiple-Hypothesis Approach to Visual Modeling and Exploration

The primary intent of this work is to present a method for sequentially associating three-dimensional surface measurements acquired by an autonomous exploration agent with models that describe those surfaces. Traditional multiple-viewpoint registration approaches are concerned only with finding the transformation that maps data points to a chosen global frame. Given a parts-based object representation, and assuming that the view correspondence can be found, the problem of associating the registered data with the correct part models still needs to be solved. While traditional approaches are content to group segmented data sets that geometrically overlap one another with the same part, there are cases where this causes ambiguous situations. This paper addresses the model-data association problem as it applies to three-dimensional dynamic object modeling. By tracking the state of part models across subsequent views, we wish to identify possible events that explain model-data association ambiguities and represent them in a Bayesian framework. The model-data association problem is therefore relaxed to allow multiple interpretations of the object's structure, each being assigned a probability. Rather than making a decision at every iteration about an ambiguous mapping, we look to the future for the information needed to disambiguate it. Experimental results are presented to illustrate the effectiveness of the approach.     

动画场景教学初探

动画场景教学在国内开展时间较短,各种教学理论、方法还在不断探索之中,针对动画场景教学中的一些问题进行积极地探索,丰富国内动画场景的教学实践。     

基于MSA直方图的景象匹配算法研究

提出了一种基于MSA直方图的景象匹配算法,用来解决景象匹配辅助导航系统中,由于拍摄的实时图背景复杂、存在畸变、易受遮挡等因素所带来的匹配困难。该算法利用灰度信息及其空间分布信息,分别计算目标区域及模板的MSA直方图,并计算匹配度,采用金字塔算法及中途停止策略进行搜索,对目标进行识别和定位。用cameraman图像、人脸图像和实际卫星拍摄图像进行了实验,实验结果表明：该算法对仿射变换、轻微透视投影变换、噪声、遮挡及视角变化具有鲁棒性,且比灰度直方图具有更好的性能,在实际拍摄的图像中能对目标进行准确的识别和定位。     

红外动态景象产生器的薄膜技术

Bly Cells的红外动态景象产生器的响应速度和空间分辨率是制约其应用的两个关键因素,并由其主要部件--转换薄膜的动态特性和空间特性所确定.以Bly Cell型薄膜红外动态景象产生器转换薄膜为研究对象,根据转换薄膜的工作原理,建立了它的动态温度分布模型,计算了其在环形脉冲源作用下的不同时刻温度场及其温度变化特性,分析了转换薄膜的动态特性和空间特性.计算结果表明,导热系数和密度越小,薄膜的表面发射率越大,则其时间响应越快;导热系数、密度、发射率越小,空间分辨率越高.     

基于多阶段多尺度彩色图像引导的道路场景深度图像补全

道路场景深度图像对于道路目标检测、智能驾驶汽车、场景3维重建等研究和应用都是至关重要的,但是由于硬件条件的限制,激光雷达获取的场景深度图像非常稀疏,道路场景深度补全旨在利用稠密的场景彩色图像指导稀疏雷达深度图像的补全重建,是目前的研究热点。该文设计了一种新型的多阶段多尺度引导的轻量化编解码网络来实现道路深度图像的高质量补全。该文网络由“彩色引导”和“精细化补全”两个阶段构成。在两个阶段的编码端,提出带有通道随机混合的轻量化多尺度卷积模块,更好地提取图像特征的同时控制网络的参数量。在两个阶段的解码端,采用通道感知机制来实现对重要特征的聚焦。同时将“彩色引导”阶段解码端的多尺度特征融合到“精细化补全”阶段的编码端中,实现多阶段多尺度的特征引导。在训练过程中,该文设计了多损失函数策略来完成由粗到细的深度图像补全。实验表明所提算法能实现高质量的深度图像补全并且具有轻量化的网络结构。