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:20250110T023312Z 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:Technical Papers\n\nAlexandre Chapiro (Reality Labs, Meta); Do ngyeon Kim (University of Cambridge); Yuta Asano (Reality Labs, Meta); and RafaƂ K. Mantiuk (University of Cambridge)\n\nThe perception of visual co ntent in optical-see-through augmented reality (AR) devices is affected by the light coming from the environment. This additional light interacts wi th the content in a non-trivial manner because of the illusion of transpar ency, different focal depths, and motion parallax. \n\nTo investigate the impact of environment light, we created the first video-quality dataset ta rgeted toward augmented reality (AR) displays. The goal was to capture the effect of AR display artifacts (such as blur, or color fringes) on video quality in the presence of a background. Our dataset consists of 6 scenes, each affected by one of 6 distortions at two strength levels, seen agains t one of 3 background patterns shown at 2 luminance levels: 432 conditions in total. Our dataset shows that the environment light has a much smaller masking effect than expected. Further, we show that this effect cannot be explained by compositing of the AR-content with the background using opti cal blending simulations. As a consequence, we demonstrate that existing v ideo quality metrics do a poor job of predicting the perceived magnitude o f degradation in AR displays, prompting the need for further research.\n\n Registration Category: Full Access, Full Access Supporter\n\nLanguage Form at: English Language\n\nSession Chair: Yifan Peng (University of Hong Kong ) URL:https://asia.siggraph.org/2024/program/?id=papers_861&sess=sess111 END:VEVENT END:VCALENDAR