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Graph."],"published-print":{"date-parts":[[2012,11]]},"abstract":"<jats:p>\n            We present a method for synthesizing 3D object arrangements from examples. Given a few user-provided examples, our system can synthesize a diverse set of plausible new scenes by learning from a larger scene database. We rely on three novel contributions. First, we introduce a\n            <jats:italic>probabilistic model for scenes<\/jats:italic>\n            based on Bayesian networks and Gaussian mixtures that can be trained from a small number of input examples. Second, we develop a clustering algorithm that groups objects occurring in a database of scenes according to their local scene neighborhoods. These\n            <jats:italic>contextual categories<\/jats:italic>\n            allow the synthesis process to treat a wider variety of objects as interchangeable. Third, we train our probabilistic model on a mix of user-provided examples and relevant scenes retrieved from the database. This\n            <jats:italic>mixed model<\/jats:italic>\n            learning process can be controlled to introduce additional variety into the synthesized scenes. We evaluate our algorithm through qualitative results and a perceptual study in which participants judged synthesized scenes to be highly plausible, as compared to hand-created scenes.\n          <\/jats:p>","DOI":"10.1145\/2366145.2366154","type":"journal-article","created":{"date-parts":[[2012,11,14]],"date-time":"2012-11-14T20:36:17Z","timestamp":1352925377000},"page":"1-11","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":265,"title":["Example-based synthesis of 3D object arrangements"],"prefix":"10.1145","volume":"31","author":[{"given":"Matthew","family":"Fisher","sequence":"first","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Ritchie","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manolis","family":"Savva","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Funkhouser","sequence":"additional","affiliation":[{"name":"Princeton University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pat","family":"Hanrahan","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2012,11]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Second International Symposium on Information Theory","volume":"1","author":"Akaike H.","year":"1973","unstructured":"Akaike , H. 1973 . 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