This paper introduces a multi-user autostereoscopic tabletop display and its associated real-time rendering methods. Tabletop displays that support both multiple viewers and autostereoscopy have been extremely difficult to construct. Our new system is inspired by the "Random Hole Display" design that modified the pattern of openings in a barrier mounted in front of a flat panel display from thin slits to a dense pattern of tiny, pseudo-randomly placed holes. This allows viewers anywhere in front of the display to see a different subset of the display’s native pixels through the random-hole screen. However, a fraction of the visible pixels will be observable by more than a single viewer. Thus the main challenge is handling these "conflicting" pixels, which ideally must show different colors to each viewer. We introduce several solutions to this problem and describe in detail the current method of choice, a combination of color blending and approximate error diffusion, performing in real time in our GPU-based implementation. The easily reproducible design uses a pattern film barrier affixed to the display by means of a transparent polycarbonate layer spacer. We use a commercial optical tracker for viewers’ locations and synthesize the appropriate image (or a stereoscopic image pair) for each viewer. The system supports graceful degradation with increasing number of simultaneous views, and graceful improvement as the number of views decreases.<\/p>\n","protected":false},"excerpt":{"rendered":"
This paper introduces a multi-user autostereoscopic tabletop display and its associated real-time rendering methods. Tabletop displays that support both multiple viewers and autostereoscopy have been extremely difficult to construct. Our new system is inspired by the "Random Hole Display" design that modified the pattern of openings in a barrier mounted in front of a flat […]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,3],"tags":[1782,633,20,436,144],"class_list":["post-5380","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-paper","tag-computer-science","tag-hardware-architecture","tag-nvidia","tag-nvidia-geforce-gtx-295","tag-rendering"],"views":1792,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5380","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=5380"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5380\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5380"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5380"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5380"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}