LEADER 02554oam 2200457zu 450 001 9910141067203321 005 20241212220147.0 010 $a9781457721854 010 $a1457721856 010 $a9781457721847 010 $a1457721848 035 $a(CKB)2670000000131685 035 $a(SSID)ssj0000669988 035 $a(PQKBManifestationID)12276044 035 $a(PQKBTitleCode)TC0000669988 035 $a(PQKBWorkID)10715839 035 $a(PQKB)11325784 035 $a(NjHacI)992670000000131685 035 $a(EXLCZ)992670000000131685 100 $a20160829d2011 uy 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$a2011 IEEE International Symposium on Mixed and Augmented Reality 210 31$a[Place of publication not identified]$cIEEE$d2011 215 $a1 online resource 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a9781457721830 311 08$a145772183X 330 $aWe present a system for accurate real-time mapping of complex and arbitrary indoor scenes in variable lighting conditions, using only a moving low-cost depth camera and commodity graphics hardware. We fuse all of the depth data streamed from a Kinect sensor into a single global implicit surface model of the observed scene in real-time. The current sensor pose is simultaneously obtained by tracking the live depth frame relative to the global model using a coarse-to-fine iterative closest point (ICP) algorithm, which uses all of the observed depth data available. We demonstrate the advantages of tracking against the growing full surface model compared with frame-to-frame tracking, obtaining tracking and mapping results in constant time within room sized scenes with limited drift and high accuracy. We also show both qualitative and quantitative results relating to various aspects of our tracking and mapping system. Modelling of natural scenes, in real-time with only commodity sensor and GPU hardware, promises an exciting step forward in augmented reality (AR), in particular, it allows dense surfaces to be reconstructed in real-time, with a level of detail and robustness beyond any solution yet presented using passive computer vision. 606 $aAugmented reality$vCongresses 615 0$aAugmented reality 676 $a006.8 702 $aIEEE Staff 801 0$bPQKB 906 $aPROCEEDING 912 $a9910141067203321 996 $a2011 IEEE International Symposium on Mixed and Augmented Reality$92308208 997 $aUNINA LEADER 02011nam 22005893 450 001 9910886980803321 005 20250905121017.0 010 $a9781003390152 010 $a1003390153 010 $a9781040153857 010 $a1040153852 024 7 $a10.4324/9781003390152 035 $a(MiAaPQ)EBC31467404 035 $a(Au-PeEL)EBL31467404 035 $a(CKB)34195557700041 035 $a(OCoLC)1453321714 035 $a(NjHacI)9934195557700041 035 $a(ScCtBLL)4c023fe7-438a-487e-852e-57ab62f48d26 035 $a(OCoLC)1454194193 035 $a(OCoLC-P)1454194193 035 $a(FlBoTFG)9781003390152 035 $a(EXLCZ)9934195557700041 100 $a20240826d2024 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAuthoritarian Populism and the Challenges for News Journalism $eA Discourse Approach 205 $a1st ed. 210 1$aOxford :$cTaylor & Francis Group,$d2024. 210 4$dİ2025. 215 $a1 online resource (187 pages) 225 1 $aPolitics, Media and Political Communication Series 311 08$a9781032486628 311 08$a1032486627 330 $aAuthoritarian Populism and the Challenges for News Journalism: A Discourse Approach is a cutting-edge study of the practices of news journalism against the background of surging authoritarian populism. 410 0$aPolitics, Media and Political Communication Series 606 $aAuthoritarianism 606 $aLanguage and languages$xPolitical aspects 615 0$aAuthoritarianism. 615 0$aLanguage and languages$xPolitical aspects. 676 $a070.44932 700 $aEkstro?m$b Mats$01768541 701 $aPatrona$b Marianna$01689175 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910886980803321 996 $aAuthoritarian Populism and the Challenges for News Journalism$94229950 997 $aUNINA