如何设定品牌标志的设计标准

品牌设计师通过知觉联想可以将文字语言转化为直接、可见的视觉图形传达给社会大众,这种语言上的转换是设计师发掘人们想象不到或想象不全面的一种表现方式,是艺术创造。同时,在没有限制,具有广泛可能性的创意、设计中,要把企业理念和目标等文字语言浓缩、整合出适合创意、设计的关键语,这一个个关键语就是品牌标志设计的依据和标准。有了这样的设计标准就会提高设计效率和准确性,减少在标志设计过程中的矛盾与摩擦,起到指引方向和检验最终方案的作用。     

浅议视觉传达设计中的“空白”

空白,也称为"虚空间",指被其他要素包围的空间。空白部分运用的好,有时则会成为设计中最突出、最令人瞩目的部分。本文就针对空白在视觉设计中的一些作用做相关的探讨。     

视觉传达设计中数字的应用及其审美

数字不仅作为一种文化现象在传播,而且作为一种符号也被高效率地再表现和再认识,它是视觉传达设计中的设计元素。本文试从数字在东西方的释义及数字在设计作品中的应用及其审美介绍入手,阐述数字在视觉传达设计中的重要性。     

城市街区空间引导系统的设计思考

城市街区空间引导系统与人们的日常生活息息相关,为人们的出行提供了便捷的标识引导,同时它也是城市形象的重要组成部分之一。本文分析总结了该系统的设计原则,并从视觉传达学科入手分析其视觉元素的设计。为了设计无语言障碍和有个性、地域化的城市街区空间引导系统,从符号、文字、色彩三方面对其进行设计思考。     

基于网页界面的视觉构成要素分析

本文主要分析了构成网页界面的视觉要素,对构成要素进行了分类,并分别对每一类要素进行了具体分析,希望能为网页界面视觉设计提供一定的参考。     

商业插画中视觉张力表现应该具有人文关怀和道德尺度

商业插画中视觉张力表现应该具有人文关怀和道德尺度。写作目的在于思索解决问题的方法,倡导创作符合大众审美品位的视觉作品。不要突兀、紧张和过分刺激,应该是积极向上的、从受众心理出发的、互动的视觉感受。创作具有视觉张力的商业插画要以人文关怀为出发点,提高文化内涵和道德修养。分析目前各个信息传达方,他们为推介产品不择手段。一味追求视觉注意,而忽视人文关怀和道德尺度。     

A referential scheme for modeling and identifying spatial attributes of entities in constructed facilities

This paper presents a referential scheme for representing and identifying the spatial extent of physical entities of constructed facilities, such as buildings and offshore structures. Using the basic operations of a non-manifold geometric modeler, a set of high-level algebraic operations is defined. The scheme and its algebra are used for modeling the spatial attributes of a facility entity at two levels: primary and secondary. The primary representation uniquely captures an entity's spatial attributes at the skeletal level and is used mainly for identifying discipline-independent topological relationships of that entity with others. Secondary representations, on the other hand, are used to provide an entity's discipline-specific geometric attributes. The topological relationships and geometric attributes of facility entities thus need not be explicitly stored, but can be computed on demand by the underlying non-manifold modeler.     

Human visual sensitivity based optimal local backlight dimming methodologies under different viewing conditions

An adaptive local backlight dimming algorithm is proposed considering human visual sensitivities under various viewing conditions. Local dimming amount is maximized based on contrast sensitivity function and local image characteristics to minimize perceived luminance and contrast losses maintaining image qualities. Average luminance, contrast and spatial frequency are evaluated as local image characteristics. As dimming based on local characteristics has blocking artifacts, a compensation method using edge luminance difference is proposed considering human responses. The proposed algorithms reduce backlight power consumption by 39.69% on average, with an average SSIM of 0.995. It can be increased by 5.66% with varying viewing conditions, resulting in a 45.35% power consumption reduction on average. The outperformances of the proposed algorithm in power consumption reduction and maintaining image quality are verified with various image quality metrics compared to recent dimming algorithms.     

VA + Embeddings STAR: A State-of-the-Art Report on the Use of Embeddings in Visual Analytics

Over the past years, an increasing number of publications in information visualization, especially within the field of visual analytics, have mentioned the term “embedding” when describing the computational approach. Within this context, embeddings are usually (relatively) low-dimensional, distributed representations of various data types (such as texts or graphs), and since they have proven to be extremely useful for a variety of data analysis tasks across various disciplines and fields, they have become widely used. Existing visualization approaches aim to either support exploration and interpretation of the embedding space through visual representation and interaction, or aim to use embeddings as part of the computational pipeline for addressing downstream analytical tasks. To the best of our knowledge, this is the first survey that takes a detailed look at embedding methods through the lens of visual analytics, and the purpose of our survey article is to provide a systematic overview of the state of the art within the emerging field of embedding visualization. We design a categorization scheme for our approach, analyze the current research frontier based on peer-reviewed publications, and discuss existing trends, challenges, and potential research directions for using embeddings in the context of visual analytics. Furthermore, we provide an interactive survey browser for the collected and categorized survey data, which currently includes 122 entries that appeared between 2007 and 2023.     

AR-based deep learning for real-time inspection of cable brackets in aircraft

In the process of aircraft assembly, there exist numerous and ubiquitous cable brackets that shall be installed on frames and subsequently need to be manually verified with CAD models. Such a task is usually performed by special operators, hence is time-consuming, labor-intensive, and error-prone. In order to save the inspection time and increase the reliability of results, many researchers attempt to develop intelligent inspection systems using robotic, AR, or AI technologies. However, there is no comprehensive method to achieve enough portability, intelligence, efficiency, and accuracy while providing intuitive task assistance for inspectors in real time. In this paper, a combined AR+AI system is introduced to assist brackets inspection in a more intelligent yet efficient manner. Especially, AR-based Mask R-CNN is proposed by skillfully integrating markerless AR into deep learning-based instance segmentation to generate more accurate and fewer region proposals, and thus alleviates the computation load of the deep learning program. Based on this, brackets segmentation can be performed robustly and efficiently on mobile devices such as smartphones or tablets. By using the proposed system, CAD model checking can be automatically performed between the segmented physical brackets and the corresponding virtual brackets rendered by AR in real time. Furthermore, the inspection results can be directly projected on the corresponding physical brackets for the convenience of maintenance. To verify the feasibility of the proposed method, experiments are carried out on a full-scale mock-up of C919 aircraft main landing gear cabin. The experimental results indicate that the inspection accuracy is up to 97.1%. Finally, the system has been deployed in the real C919 aircraft final-assembly workshop. The preliminary evaluation reveals that the proposed real-time AR-assisted intelligent inspection approach is effective and promising for large-scale industrial applications.