BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:Asia/Tokyo
X-LIC-LOCATION:Asia/Tokyo
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:JST
DTSTART:18871231T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260817T171531Z
LOCATION:Hall B7 (1)\, B Block\, Level 7
DTSTART;TZID=Asia/Tokyo:20241203T171600
DTEND;TZID=Asia/Tokyo:20241203T172800
UID:siggraphasia_SIGGRAPH Asia 2024_sess111_papers_861@linklings.com
SUMMARY:AR-DAVID: Augmented Reality Display Artifact Video Dataset
DESCRIPTION:Alexandre Chapiro (Reality Labs, Meta); Dongyeon Kim (Universi
 ty of Cambridge); Yuta Asano (Reality Labs, Meta); and Rafał K. Mantiuk (U
 niversity of Cambridge)\n\nThe perception of visual content in optical-see
 -through augmented reality (AR) devices is affected by the light coming fr
 om the environment. This additional light interacts with the content in a 
 non-trivial manner because of the illusion of transparency, different foca
 l depths, and motion parallax. \n\nTo investigate the impact of environmen
 t light, we created the first video-quality dataset targeted toward augmen
 ted reality (AR) displays. The goal was to capture the effect of AR displa
 y artifacts (such as blur, or color fringes) on video quality in the prese
 nce of a background. Our dataset consists of 6 scenes, each affected by on
 e of 6 distortions at two strength levels, seen against one of 3 backgroun
 d patterns shown at 2 luminance levels: 432 conditions in total. Our datas
 et shows that the environment light has a much smaller masking effect than
  expected. Further, we show that this effect cannot be explained by compos
 iting of the AR-content with the background using optical blending simulat
 ions. As a consequence, we demonstrate that existing video quality metrics
  do a poor job of predicting the perceived magnitude of degradation in AR 
 displays, prompting the need for further research.\n\nRegistration Categor
 y: Full Access, Full Access Supporter\n\nLanguage Format: English Language
 \n\nSession Chair: Yifan Peng (The University of Hong Kong)\n\n
URL:https://asia.siggraph.org/2024/program/?id=papers_861&sess=sess111
END:VEVENT
END:VCALENDAR