{"id":10471,"date":"2024-03-03T15:35:29","date_gmt":"2024-03-03T15:35:29","guid":{"rendered":"https:\/\/dailyai.com\/?p=10471"},"modified":"2024-03-04T11:20:05","modified_gmt":"2024-03-04T11:20:05","slug":"-4","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nb\/2024\/03\/-4\/","title":{"rendered":"Forskere bygger syntetiske hundedatasett i GTA-V for \u00e5 lage 3D-modeller"},"content":{"rendered":"

Forskere fra University of Surrey har utviklet en metode for \u00e5 forvandle fotografier av hunder til detaljerte 3D-modeller.\u00a0<\/b><\/p>\n

Treningsmateriellet? Ikke ekte hunder, men datagenererte bilder fra den virtuelle verdenen i det popul\u00e6re spillet Grand Theft Auto V (GTA V).\u00a0<\/span><\/p>\n

Moira Shooter, en doktorgradsstudent som deltok i studien, <\/span>delt av studien<\/span><\/a>\"Modellen v\u00e5r ble trent opp p\u00e5 CGI-hunder - men vi kunne bruke den til \u00e5 lage 3D-skjelettmodeller fra fotografier av ekte dyr. Det kan gj\u00f8re det mulig for naturvernere \u00e5 oppdage skadde dyr, eller hjelpe kunstnere med \u00e5 skape mer realistiske dyr i metaverse.\"<\/span><\/p>\n

Hittil har metoder for \u00e5 l\u00e6re kunstig intelligens om 3D-strukturer g\u00e5tt ut p\u00e5 \u00e5 bruke ekte bilder sammen med data om objektenes faktiske 3D-posisjoner, ofte innhentet ved hjelp av motion capture-teknologi.\u00a0<\/span><\/p>\n

Men n\u00e5r man bruker disse teknikkene p\u00e5 hunder eller andre dyr, er det ofte for mange bevegelser \u00e5 spore, og det er vanskelig \u00e5 f\u00e5 hundene til \u00e5 oppf\u00f8re seg lenge nok.\u00a0<\/span><\/p>\n

For \u00e5 bygge hundedatasettet endret forskerne GTA V-koden for \u00e5 erstatte de menneskelige karakterene med hundeavatarer gjennom en prosess kjent som \"modding\".\u00a0<\/span><\/p>\n

\"Hunder\"
Eksempler fra det syntetiske hundedatasettet generert ved hjelp av GTA-V. Kilde: Universitetet i Surrey<\/a>.<\/figcaption><\/figure>\n

Forskerne produserte 118 videoer der de virtuelle hundene ble filmet i ulike situasjoner - sittende, g\u00e5ende, bjeffende og l\u00f8pende - under ulike milj\u00f8forhold. <\/span><\/p>\n

Dette kulminerte i opprettelsen av \"DigiDogs\", en rikholdig database som inneholder 27 900 bilder av hundens bevegelser, fanget opp p\u00e5 en m\u00e5te som datainnsamlingen i den virkelige verden ikke hadde tillatt.<\/span><\/p>\n

Med datasettet i h\u00e5nden ble Metas DINOv2 AI-modell brukt for sine sterke generaliseringsevner, og den ble finjustert med DigiDogs for \u00e5 forutsi 3D-positurer n\u00f8yaktig fra RGB-bilder med \u00e9n visning.<\/span><\/p>\n

Forskerne demonstrerte at bruk av DigiDogs datasett for trening resulterte i mer n\u00f8yaktige og naturtro 3D-hundepositurer enn de som ble trent p\u00e5 virkelige datasett, takket v\u00e6re variasjonen i hundenes utseende og handlinger. <\/span><\/p>\n

Modellens forbedrede ytelse ble bekreftet gjennom grundige kvalitative og kvantitative evalueringer.<\/span><\/p>\n

\"AI-hunder\"
Modeller trent p\u00e5 det syntetiske datasettet DigiDogs viste bedre n\u00f8yaktighet enn de som kun var trent med det virkelige datasettet RGBD-Dogs. Du kan se dette her hvis du ser n\u00f8ye p\u00e5 de forventede tilordningene (i rosa) i forhold til sannheten (i gr\u00f8nt), som er forbedret p\u00e5 h\u00f8yre side. Kilde: Universitetet i Surrey<\/a>.<\/figcaption><\/figure>\n

Selv om denne studien representerte et stort skritt fremover innen 3D-dyremodellering, erkjenner teamet at det er mer arbeid som m\u00e5 gj\u00f8res, spesielt n\u00e5r det gjelder \u00e5 forbedre hvordan modellen forutsier dybdeaspektet i bildene (z-koordinaten).\u00a0<\/span><\/p>\n

Shooter beskrev den potensielle effekten av arbeidet deres og sa: \"3D-fotografier inneholder s\u00e5 mye mer informasjon enn 2D-fotografier. Denne smarte l\u00f8sningen har s\u00e5 mange mulige bruksomr\u00e5der, fra \u00f8kologi til animasjon.\"<\/span><\/p>\n

Den <\/span>papir<\/span><\/a> vant prisen for beste artikkel p\u00e5 IEEE\/CVF Winter Conference on Applications of Computer Vision. <\/span><\/p>\n

Det \u00e5pner for bedre modellytelse p\u00e5 omr\u00e5der som bevaring av dyreliv og 3D-objektgjengivelse for VR.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

Forskere fra University of Surrey har utviklet en metode for \u00e5 forvandle fotografier av hunder til detaljerte 3D-modeller. Treningsmateriellet? Ikke ekte hunder, men datagenererte bilder fra den virtuelle verdenen i det popul\u00e6re spillet Grand Theft Auto V (GTA V). Moira Shooter, en doktorgradsstudent som deltok i studien, forteller: \"Modellen v\u00e5r ble trent opp p\u00e5 CGI-hunder - men vi kunne bruke den til \u00e5 lage 3D-skjelettmodeller av fotografier av ekte dyr. Det kan gj\u00f8re det mulig for naturvernere \u00e5 oppdage skadde dyr, eller hjelpe kunstnere med \u00e5 skape mer realistiske dyr i metaverse.\" Til<\/p>","protected":false},"author":2,"featured_media":10474,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[105,546],"class_list":["post-10471","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-machine-learning","tag-vr"],"yoast_head":"\nResearchers build synthetic dog dataset in GTA-V to create 3D models | DailyAI<\/title>\n<meta name=\"description\" content=\"Researchers from the University of Surrey have developed a method to transform photographs of dogs into detailed 3D models.\u00a0\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/nb\/2024\/03\/-4\/\" 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