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Structure Perception in 3D Point Clouds

Conference ·
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Understanding human perception is critical to the design of effective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the literature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projections of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rotation, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under rotation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns perceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE); USDOE Office of Science (SC), Office of Workforce Development for Teachers and Scientists (WDTS), Science Undergraduate Laboratory Internship (SULI) Program; USDOE National Renewable Energy Laboratory (NREL), Laboratory Directed Research and Development (LDRD) Program
DOE Contract Number:
AC36-08GO28308
OSTI ID:
1826120
Report Number(s):
NREL/CP-2C00-81217; MainId:81990; UUID:26b90914-6faa-4198-b838-02e365239957; MainAdminID:63170
Resource Relation:
Conference: Presented at SAP '21: ACM Symposium on Applied Perception 2021, 16-17 September 2021
Country of Publication:
United States
Language:
English

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MATHEMATICS AND COMPUTING
data analysis
data visualization
encoding
human factors
image generation
scatterplots
visual perception