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BEGIN:VEVENT
UID:a1b6ff5cabc9d3099d937d20866501136f04bfa2@swoogo.com
DTSTAMP:20260909T121952Z
DESCRIPTION:In digital content creation\, accurately assessing image and vi
 deo quality is essential to preserve the creator's original intent. Tradit
 ional evaluation methods often overlook the unique aspects of rendering sy
 stems or focus only on display monitor specifications\, missing the viewer
 's perceptual experience. This study introduces a comprehensive framework 
 that addresses these limitations by integrating a transmission channel mod
 el and a human perception model. The transmission channel model simulates 
 how visual content is processed and displayed\, considering the rendering 
 device's capabilities and constraints. The human perception model predicts
  how viewers interpret the content\, factoring in color fidelity\, brightn
 ess\, contrast\, and texture. By combining these models\, the framework of
 fers a more holistic evaluation of content quality\, assessing how well th
 e displayed content aligns with the creators' vision and viewer satisfacti
 on. Tested against a subject-rated database\, the framework demonstrated s
 uperior performance in predicting viewer satisfaction\, providing a valuab
 le tool for content creators\, display manufacturers\, and researchers.
DTSTART:20241022T194500Z
DTEND:20241022T201500Z
LAST-MODIFIED:20260909T121952Z
LOCATION:Session Room 1
SEQUENCE:0
STATUS:CONFIRMED
SUMMARY:Towards an Objective Metric for Preserving Creative Intent Across D
 isplays
TRANSP:OPAQUE
X-ALT-DESC;FMTTYPE=text/html:<p>In digital content creation\, accurately as
 sessing image and video quality is essential to preserve the creator's ori
 ginal intent. Traditional evaluation methods often overlook the unique asp
 ects of rendering systems or focus only on display monitor specifications\
 , missing the viewer's perceptual experience. This study introduces a comp
 rehensive framework that addresses these limitations by integrating a tran
 smission channel model and a human perception model. The transmission chan
 nel model simulates how visual content is processed and displayed\, consid
 ering the rendering device's capabilities and constraints. The human perce
 ption model predicts how viewers interpret the content\, factoring in colo
 r fidelity\, brightness\, contrast\, and texture. By combining these model
 s\, the framework offers a more holistic evaluation of content quality\, a
 ssessing how well the displayed content aligns with the creators' vision a
 nd viewer satisfaction. Tested against a subject-rated database\, the fram
 ework demonstrated superior performance in predicting viewer satisfaction\
 , providing a valuable tool for content creators\, display manufacturers\,
  and researchers.</p>
BEGIN:VALARM
UID:61623266-3336-4464-b933-656265363965
ACTION:DISPLAY
DESCRIPTION:In digital content creation\, accurately assessing image and vi
 deo quality is essential to preserve the creator's original intent. Tradit
 ional evaluation methods often overlook the unique aspects of rendering sy
 stems or focus only on display monitor specifications\, missing the viewer
 's perceptual experience. This study introduces a comprehensive framework 
 that addresses these limitations by integrating a transmission channel mod
 el and a human perception model. The transmission channel model simulates 
 how visual content is processed and displayed\, considering the rendering 
 device's capabilities and constraints. The human perception model predicts
  how viewers interpret the content\, factoring in color fidelity\, brightn
 ess\, contrast\, and texture. By combining these models\, the framework of
 fers a more holistic evaluation of content quality\, assessing how well th
 e displayed content aligns with the creators' vision and viewer satisfacti
 on. Tested against a subject-rated database\, the framework demonstrated s
 uperior performance in predicting viewer satisfaction\, providing a valuab
 le tool for content creators\, display manufacturers\, and researchers.
TRIGGER:-PT15M
END:VALARM
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