Knowledge communication at the computer-human interface requires discovering, understanding, comparing, and communicating patterns in data, maps, and diagrams. Those patterns are ubiquitously transmitted via static visual displays. Dynamic displays are increasingly used to effectively leverage the processing power of the human visual system: to show the evolution of two populations, to translate among multiple views of a map, or show the same data across different perspectives, axes, or projections. In theory, dynamic displays should be a highly efficient way to transfer information to human minds – but they instead tend to overwhelm, confuse, or misinform. Existing guidelines for the use of motion are not strongly informed by the perceptual limitations of the human observers of these dynamic patterns. The goal of this work is to determine the perceptual capacity limitations within these dynamic displays. By focusing on human performance for information extraction from dynamic charts and maps, we will produce a perceptual model of why and when visual processing succeeds or fails in dynamic displays. This model will lead to perception-informed guidelines that allow designers to construct efficient displays for their viewers.
|Effective start/end date||10/1/21 → 9/30/24|
- National Science Foundation (IIS-2107490-001)
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