{"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":"researchers-build-synthetic-dog-dataset-in-gta-v-to-create-3d-models","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nl\/2024\/03\/researchers-build-synthetic-dog-dataset-in-gta-v-to-create-3d-models\/","title":{"rendered":"Onderzoekers bouwen synthetische hondendataset in GTA-V om 3D-modellen te maken"},"content":{"rendered":"

Onderzoekers van de Universiteit van Surrey hebben een methode ontwikkeld om foto's van honden om te zetten in gedetailleerde 3D-modellen.\u00a0<\/b><\/p>\n

Het trainingsmateriaal? Geen echte honden, maar computergegenereerde beelden uit de virtuele wereld van het hitspel Grand Theft Auto V (GTA V).\u00a0<\/span><\/p>\n

Moira Shooter, een postdoctorale onderzoeksstudent betrokken bij het onderzoek, <\/span>gedeeld door het onderzoek<\/span><\/a>Ons model werd getraind op CGI-honden, maar we konden het gebruiken om 3D-skeletmodellen te maken van foto's van echte dieren. Dat zou natuurbeschermers in staat kunnen stellen om gewonde wilde dieren te spotten, of kunstenaars kunnen helpen om realistischere dieren te cre\u00ebren in het metaversum.\"<\/span><\/p>\n

Tot nu toe worden bij methodes om AI te leren over 3D-structuren echte foto's gebruikt naast gegevens over de werkelijke 3D-posities van objecten, vaak verkregen met behulp van motion capture-technologie.\u00a0<\/span><\/p>\n

Als je deze technieken echter toepast op honden of andere dieren, zijn er vaak te veel bewegingen om te volgen en is het moeilijk om honden zich lang genoeg te laten gedragen.\u00a0<\/span><\/p>\n

Om hun hondendataset samen te stellen, pasten de onderzoekers de code van GTA V aan om de menselijke personages te vervangen door hondenavatars via een proces dat bekend staat als \"modding\".\u00a0<\/span><\/p>\n

\"Honden\"
Voorbeelden van de synthetische hondendataset gegenereerd met GTA-V. Bron: Universiteit van Surrey<\/a>.<\/figcaption><\/figure>\n

Onderzoekers produceerden 118 video's die deze virtuele honden vastlegden in verschillende acties - zitten, lopen, blaffen en rennen - in verschillende omgevingsomstandigheden. <\/span><\/p>\n

Dit culmineerde in de creatie van 'DigiDogs', een rijke database met 27.900 frames van hondenbewegingen, vastgelegd op een manier waarop het verzamelen van gegevens in de echte wereld niet mogelijk was.<\/span><\/p>\n

Met de dataset in de hand werd in de volgende stappen het DINOv2 AI-model van Meta gebruikt vanwege zijn sterke generalisatievaardigheden. Dit model werd verfijnd met DigiDogs om nauwkeurig 3D-houdingen te voorspellen op basis van RGB-afbeeldingen met \u00e9\u00e9n weergave.<\/span><\/p>\n

Onderzoekers toonden aan dat het gebruik van de DigiDogs dataset voor training resulteerde in accuratere en levensechtere 3D honden poses dan die getraind op echte datasets, dankzij de variatie in hondenverschijningen en acties die werden vastgelegd. <\/span><\/p>\n

De verbeterde prestaties van het model werden bevestigd door grondige kwalitatieve en kwantitatieve evaluaties.<\/span><\/p>\n

\"AI
Modellen die zijn getraind op de synthetische dataset DigiDogs lieten een betere nauwkeurigheid zien dan modellen die alleen zijn getraind met de echte dataset RGBD-Dogs. U kunt dit hier zien als u goed kijkt naar de voorspelde toewijzingen (in roze) versus de grondwaarheid (in groen), die aan de rechterkant zijn verbeterd. Bron: Universiteit van Surrey<\/a>.<\/figcaption><\/figure>\n

Hoewel dit onderzoek een grote stap voorwaarts betekent in het modelleren van 3D-dieren, erkent het team dat er nog meer werk te doen is, vooral in het verbeteren van de manier waarop het model het diepteaspect van de beelden (de z-co\u00f6rdinaat) voorspelt.\u00a0<\/span><\/p>\n

Shooter beschreef de potenti\u00eble impact van hun werk door te zeggen: \"3D poses bevatten zoveel meer informatie dan 2D foto's. Van ecologie tot animatie. Van ecologie tot animatie, deze nette oplossing heeft zoveel mogelijke toepassingen.\"<\/span><\/p>\n

De <\/span>papier<\/span><\/a> won de prijs voor de beste paper op de IEEE\/CVF Winter Conference on Applications of Computer Vision. <\/span><\/p>\n

Het opent de deur naar betere modelprestaties op gebieden zoals natuurbehoud en 3D-objectrendering voor VR.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

Onderzoekers van de Universiteit van Surrey hebben een methode ontwikkeld om foto's van honden om te zetten in gedetailleerde 3D-modellen. Het trainingsmateriaal? Geen echte honden, maar computergegenereerde beelden uit de virtuele wereld van het hitspel Grand Theft Auto V (GTA V). Moira Shooter, een postdoctorale onderzoeksstudent die betrokken was bij het onderzoek, zei over het onderzoek: \"Ons model werd getraind op CGI-honden, maar we konden het gebruiken om 3D-skeletmodellen te maken van foto's van echte dieren. Dat zou natuurbeschermers in staat kunnen stellen om gewonde wilde dieren op te sporen of kunstenaars kunnen helpen om realistischere dieren te cre\u00ebren in het metaversum.\" Naar<\/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\" 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