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TZID:Asia/Hong_Kong
X-LIC-LOCATION:Asia/Hong_Kong
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DTSTART:19911015T033000
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BEGIN:VEVENT
DTSTAMP:20251218T030657Z
LOCATION:Meeting Room S423+S424\, Level 4
DTSTART;TZID=Asia/Hong_Kong:20251216T104000
DTEND;TZID=Asia/Hong_Kong:20251216T105000
UID:siggraphasia_SIGGRAPH Asia 2025_sess117_papers_1077@linklings.com
SUMMARY:CameraVDP: Perceptual Display Assessment with Uncertainty Estimati
 on via Camera and Visual Difference Prediction
DESCRIPTION:Yancheng Cai (University of Cambridge), Robert Wanat (LG Elect
 ronics North America), and Rafal Mantiuk (University of Cambridge)\n\nAccu
 rate measurement of images produced by electronic displays is critical for
  the evaluation of both traditional and computational displays. Traditiona
 l display measurement methods based on sparse radiometric sampling and fit
 ting a model are inadequate for capturing spatially varying display artifa
 cts, as they fail to capture high-frequency and pixel-level distortions. W
 hile cameras offer sufficient spatial resolution, they introduce optical, 
 sampling, and photometric distortions. Furthermore, the physical measureme
 nt must be combined with a model of a visual system to assess whether the 
 distortions are going to be visible. To enable perceptual assessment of di
 splays, we propose a combination of a camera-based reconstruction pipeline
  with a visual difference predictor, which account for both the inaccuracy
  of camera measurements and visual difference prediction. The reconstructi
 on pipeline combines HDR image stacking, MTF inversion, vignetting correct
 ion, geometric undistortion, homography transformation, and color correcti
 on, enabling cameras to function as precise display measurement instrument
 s. By incorporating a Visual Difference Predictor (VDP), our system models
  the visibility of various stimuli under different viewing conditions for 
 the human visual system. We validate the proposed CameraVDP framework thro
 ugh three applications: defective pixel detection, color fringing awarenes
 s, and display non-uniformity evaluation. Our uncertainty analysis framewo
 rk enables the estimation of the theoretical upper bound for defect pixel 
 detection performance and provides confidence intervals for VDP quality sc
 ores. Our code is available on https://github.com/gfxdisp/CameraVDP.\n\nRe
 gistration Category: Full Access, Full Access Supporter\n\nSession Chair: 
 Qiang Fu (King Abdullah University of Science and Technology (KAUST))\n\n
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