Yotam Erel, Or Kozlovsky-Mordenfeld, Daisuke Iwai, Kosuke Sato, Amit H. Bermano
{"title":"Casper DPM:串联感知动态投影映射到手上","authors":"Yotam Erel, Or Kozlovsky-Mordenfeld, Daisuke Iwai, Kosuke Sato, Amit H. Bermano","doi":"arxiv-2409.04397","DOIUrl":null,"url":null,"abstract":"We present a technique for dynamically projecting 3D content onto human hands\nwith short perceived motion-to-photon latency. Computing the pose and shape of\nhuman hands accurately and quickly is a challenging task due to their\narticulated and deformable nature. We combine a slower 3D coarse estimation of\nthe hand pose with high speed 2D correction steps which improve the alignment\nof the projection to the hands, increase the projected surface area, and reduce\nperceived latency. Since our approach leverages a full 3D reconstruction of the\nhands, any arbitrary texture or reasonably performant effect can be applied,\nwhich was not possible before. We conducted two user studies to assess the\nbenefits of using our method. The results show subjects are less sensitive to\nlatency artifacts and perform faster and with more ease a given associated task\nover the naive approach of directly projecting rendered frames from the 3D pose\nestimation. We demonstrate several novel use cases and applications.","PeriodicalId":501174,"journal":{"name":"arXiv - CS - Graphics","volume":"60 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Casper DPM: Cascaded Perceptual Dynamic Projection Mapping onto Hands\",\"authors\":\"Yotam Erel, Or Kozlovsky-Mordenfeld, Daisuke Iwai, Kosuke Sato, Amit H. Bermano\",\"doi\":\"arxiv-2409.04397\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a technique for dynamically projecting 3D content onto human hands\\nwith short perceived motion-to-photon latency. Computing the pose and shape of\\nhuman hands accurately and quickly is a challenging task due to their\\narticulated and deformable nature. We combine a slower 3D coarse estimation of\\nthe hand pose with high speed 2D correction steps which improve the alignment\\nof the projection to the hands, increase the projected surface area, and reduce\\nperceived latency. Since our approach leverages a full 3D reconstruction of the\\nhands, any arbitrary texture or reasonably performant effect can be applied,\\nwhich was not possible before. We conducted two user studies to assess the\\nbenefits of using our method. The results show subjects are less sensitive to\\nlatency artifacts and perform faster and with more ease a given associated task\\nover the naive approach of directly projecting rendered frames from the 3D pose\\nestimation. We demonstrate several novel use cases and applications.\",\"PeriodicalId\":501174,\"journal\":{\"name\":\"arXiv - CS - Graphics\",\"volume\":\"60 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Graphics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.04397\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Graphics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.04397","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present a technique for dynamically projecting 3D content onto human hands
with short perceived motion-to-photon latency. Computing the pose and shape of
human hands accurately and quickly is a challenging task due to their
articulated and deformable nature. We combine a slower 3D coarse estimation of
the hand pose with high speed 2D correction steps which improve the alignment
of the projection to the hands, increase the projected surface area, and reduce
perceived latency. Since our approach leverages a full 3D reconstruction of the
hands, any arbitrary texture or reasonably performant effect can be applied,
which was not possible before. We conducted two user studies to assess the
benefits of using our method. The results show subjects are less sensitive to
latency artifacts and perform faster and with more ease a given associated task
over the naive approach of directly projecting rendered frames from the 3D pose
estimation. We demonstrate several novel use cases and applications.