Journal
ACM TRANSACTIONS ON APPLIED PERCEPTION
Volume 7, Issue 2, Pages -Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/1670671.1670676
Keywords
Algorithms; Human Factors; Verification; Visual perception; mesh saliency; eye-tracker
Categories
Funding
- NSF [IIS 04-14699, CCF 04-29753, CNS 04-03313, CCF 05-41120, CMMI 08-35572]
- ARO [W911NF-08-1-0466]
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Mesh saliency has been proposed as a computational model of perceptual importance for meshes, and it has been used in graphics for abstraction, simplification, segmentation, illumination, rendering, and illustration. Even though this technique is inspired by models of low-level human vision, it has not yet been validated with respect to human performance. Here, we present a user study that compares the previous mesh saliency approaches with human eye movements. To quantify the correlation between mesh saliency and fixation locations for 3D rendered images, we introduce the normalized chance-adjusted saliency by improving the previous chance-adjusted saliency measure. Our results show that the current computational model of mesh saliency can model human eye movements significantly better than a purely random model or a curvature-based model.
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