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Electrical Engineering and Systems Science > Signal Processing

arXiv:2212.03854 (eess)
[Submitted on 7 Dec 2022 (v1), last revised 3 Jan 2024 (this version, v3)]

Title:BiPMAP: A Toolbox for Predictions of Perceived Motion Artifacts on Modern Displays

Authors:Guanghan Meng, Dekel Galor, Laura Waller, Martin S. Banks
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Abstract:Presenting dynamic scenes without incurring motion artifacts visible to observers requires sustained effort from the display industry. A tool that predicts motion artifacts and simulates artifact elimination through optimizing the display configuration is highly desired to guide the design and manufacture of modern displays. Despite the popular demands, there is no such tool available in the market. In this study, we deliver an interactive toolkit, Binocular Perceived Motion Artifact Predictor (BiPMAP), as an executable file with GPU acceleration. BiPMAP accounts for an extensive collection of user-defined parameters and directly visualizes a variety of motion artifacts by presenting the perceived continuous and sampled moving stimuli side-by-side. For accurate artifact predictions, BiPMAP utilizes a novel model of the human contrast sensitivity function to effectively imitate the frequency modulation of the human visual system. In addition, BiPMAP is capable of deriving various in-plane motion artifacts for 2D displays and depth distortion in 3D stereoscopic displays.
Comments: 11 pages, 9 figures
Subjects: Signal Processing (eess.SP); Human-Computer Interaction (cs.HC); Quantitative Methods (q-bio.QM)
Cite as: arXiv:2212.03854 [eess.SP]
  (or arXiv:2212.03854v3 [eess.SP] for this version)
  https://doi.org/10.48550/arXiv.2212.03854

Submission history

From: Guanghan Meng [view email]
[v1] Wed, 7 Dec 2022 18:51:24 UTC (7,759 KB)
[v2] Thu, 21 Sep 2023 05:44:41 UTC (28,683 KB)
[v3] Wed, 3 Jan 2024 18:05:42 UTC (23,083 KB)
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