{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T23:43:19Z","timestamp":1776469399756,"version":"3.51.2"},"reference-count":72,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2017,9,1]],"date-time":"2017-09-01T00:00:00Z","timestamp":1504224000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>An understanding of guidance, which means guiding attention, and constancy, meaning that an area can be perceived for what it is despite environmental changes, of the visual variables related to three-dimensional (3D) symbols is essential to ensure rapid and consistent human perception in 3D visualization. Previous studies have focused on the guidance and constancy of visual variables related to two-dimensional (2D) symbols, but these aspects are not well documented for 3D symbols. In this study, we used eye tracking to analyze the visual guidance from shapes, hues and sizes, and the visual constancy that is related to the shape, color saturation and size of 3D symbols in different locations. Thirty-six subjects (24 females and 12 males) participated in the study. The results indicate that hue and shape provide a high level of visual guidance, whereas guidance from size, a variable that predominantly guides attention in 2D visualization, is much more limited in 3D visualization. Additionally, constancy of shape and saturation are perceived with relatively high accuracy, whereas constancy of size is perceived with only low accuracy. These first empirical studies are intended to pave the way for a more comprehensive user understanding of 3D visualization design.<\/jats:p>","DOI":"10.3390\/ijgi6090274","type":"journal-article","created":{"date-parts":[[2017,9,1]],"date-time":"2017-09-01T11:05:24Z","timestamp":1504263924000},"page":"274","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Using Eye Tracking to Explore the Guidance and Constancy of Visual Variables in 3D Visualization"],"prefix":"10.3390","volume":"6","author":[{"given":"Bing","family":"Liu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Research Center of Geospatial Cognition and Visual Analytics, and Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Weihua","family":"Dong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Research Center of Geospatial Cognition and Visual Analytics, and Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Liqiu","family":"Meng","sequence":"additional","affiliation":[{"name":"Technical University of Munich, Munich 80333, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2017,9,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Kersting, O., and Dollner, J. 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