## 3 Related Work  
For the development of this research, studies with the following characteristics were analyzed: tests of visual variable perception, object recognition with partial overlap, and applications or techniques that utilize partially overlapping visual objects. Studies that aimed to mitigate the impact of partial overlap were not selected. [PERSON] and [PERSON] [28] evaluated two overlapping approaches based on the circle size. In the first approach, the overlapping circles were cut to fit together (sectioned), and, in the second, the transparency technique was applied to the overlapping circles. As a result, it was observed that the transparency proposal performed better. It is noteworthy that, in this study, the authors evaluated techniques for addressing the overlap problem, but did not consider different visual variables or overlap levels. [PERSON] [29] conducted perception tests in research using ten visual variables (common scale position, position unaligned scale, length, direction, angle, area, volume, curvature, shading, and saturation) to determine which visual variables best represented a set of quantitative data. In this study, the authors conducted an evaluation of visual perception of visual variables but did not account for the overlapping problem. The number of visual variables analyzed was a strength. The authors in [21] presented another classification based on visual perception evaluations using 12 visual variables (position, length, angle, slope, area, volume, density, saturation, hue, texture, connection, containment, and shape). The classification was organized using three categories of data: quantitative, ordinal, and categorical. For the study proposal in this paper, we focused only on visual variables mapped as categorical data. In this study, the authors of the visual perception tests did not consider the overlapping problem. [PERSON] [30] described the challenges of visualizing structural changes in hierarchical techniques. The author suggested combining hue and shape visual variables to represent the leaf nodes in a tree diagram. Even with the proposed overlap treatment in mind, the study did not analyze multiple levels of overlap and utilized just a few types of visual variables. In the research presented by [23], an analysis was conducted based on visual perception tests involving visual variables when applied to tasks of selection, association, ordering, etc. [PERSON] [17] was the source for the visual variables used. With regard to the findings presented in this article, a high level of visual perception was observed for the hue, texture, and orientation visual variables when used in selection tasks. Even though the authors of these studies did not conduct analyses regarding the overlapping problem, these studies are fundamental to the field of analysis of visual perception and visual variables. [PERSON] [23] conducted visual perception tests involving visual variables in tasks involving selection, association, ordering, etc. [PERSON] [17] was the source for the visual variables used. A high level of visual perception for the hue, texture, and orientation visual variables when used in selection tasks was highlighted. [PERSON] [31] proposed multidimensional glyphs to depict information with respect to a cinematographic dataset, where each component of the glyph represented a function performed by a member of a film's cast. The author created glyphs that were composed of varied overlapping elements (shapes), and each inserted element encoded a dataset attribute. The multidimensional glyphs effectively expanded the visual mapping of the additional base attributes, but the issue of overlapping glyph elements was not analyzed. [PERSON] [32] applied multidimensional glyphs in Venn and Euler diagrams. The author analyzed how combined hue and texture visual variables affected the user's visual perception. The results obtained indicated that the use of multidimensional glyphs for visual mapping of multiple attributes of a dataset can be effective.