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Correlating Low-Level Image Statistics with Users ’ Rapid Aesthetic and Affective Judgments of Web Pages

By Xianjun Sam Zheng, Ishani Chakraborty and James Jeng-weei Lin


In this paper, we report a study that examines the relationship between image-based computational analyses of web pages and users ’ aesthetic judgments about the same image material. Web pages were iteratively decomposed into quadrants of minimum entropy (quadtree decomposition) based on low-level image statistics, to permit a characterization of these pages in terms of their respective organizational symmetry, balance and equilibrium. These attributes were then evaluated for their correlation with human participants ’ subjective ratings of the same web pages on four aesthetic and affective dimensions. Several of these correlations were quite large and revealed interesting patterns in the relationship between low-level (i.e., pixel-level) image statistics and designrelevant dimensions. Author Keywords Low-level features; image statistics; computer vision; user interface design; aesthetic judgments; empirical methods ACM Classification Keywords H5.2. Information interfaces and presentation (e.g., HCI): User interfaces. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee

Year: 2009
DOI identifier: 10.1145/1518701.1518703
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
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