Feasibility and Effectiveness of 2D Highlighting Methods Applied in 3D Modeling

Abstract

The requirements for human-computer interaction in digitalized 3D production line systems are increasing in combination with the advancement of intelligent manufacturing research. However, there is a dearth of interaction research on these systems, particularly about information highlighting. This work examines the viability and impact of utilizing 2D highlighting techniques on 3D models inside digitalized 3D manufacturing line systems. A reintegrated classification method for visual variables is proposed, and the consequences and properties of static visual variables applied to 3D maps are addressed in detail. 3D highlighting methods summarized based on the 2D highlighting guidelines proposed by Robinson A. are scored by an expert scoring method. Which resulted in the selection of three highlighting methods: hue, transparency, and texture. Experiments were conducted on the three selected highlighting methods to examine the feasibility of utilizing 2D visual variables in 3D models and the impact of three variables - hue, texture, and transparency - on highlighting effects in 3D models. All three highlighting methods attracted the attention of the subjects because there was no significant difference in the effect of the different highlighting methods on reaction time(RT). Additionally, the correlation coefficient between the highlighting methods and the mean RT was the smallest, and the number of symbols and the type of symbols highlighted had a significant effect on RT. At the same time, the error rates associated with the three highlighting methods were relatively small, and the mean score of all the methods on the subjective questionnaire was above 3 points. This shows that the three highlighting methods have no problem in effectively highlighting. Objective data analysis shows that there is no doubt that the hue highlighting method has the best highlighting effect, and the transparency highlighting method has the worst effect, because transparency has the highest error rate in terms of both response time and error rate, and it has the worst efficiency among different types and numbers of highlighting symbols. Additionally, the subjective evaluation results confirm that transparency received the lowest score in terms of subjective evaluation. The outcomes of the experiments demonstrate how well these strategies work to lower error rates and increase search efficiency. At the same time, a set of guidelines applicable to 3D highlighting is summarized: saliency, ease of realization, and reduction of visual target complexity. But still, the study also identifies certain drawbacks and suggests areas for future investigation. These include examining the effects of dynamic variables and other perceptual channels on highlighting, contrasting the highlighting techniques in various target environments, and confirming the viability and efficacy of the methods. The investigation and assessment of visualization highlighting techniques for 3D models in digital 3D manufacturing line systems offered by this work is helpful.

Keywords: Digital twin, 3D production line, Highlighting, hue, texture, transparency

DOI: 10.54941/ahfe1004531