{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T19:17:28Z","timestamp":1771701448239,"version":"3.50.1"},"reference-count":34,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2011,7,1]],"date-time":"2011-07-01T00:00:00Z","timestamp":1309478400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Graph."],"published-print":{"date-parts":[[2011,7]]},"abstract":"<jats:p>Modeling virtual environments is a time consuming and expensive task that is becoming increasingly popular for both professional and casual artists. The model density and complexity of the scenes representing these virtual environments is rising rapidly. This trend suggests that data-mining a 3D scene corpus could be a very powerful tool enabling more efficient scene design. In this paper, we show how to represent scenes as graphs that encode models and their semantic relationships. We then define a kernel between these relationship graphs that compares common virtual substructures in two graphs and captures the similarity between their corresponding scenes. We apply this framework to several scene modeling problems, such as finding similar scenes, relevance feedback, and context-based model search. We show that incorporating structural relationships allows our method to provide a more relevant set of results when compared against previous approaches to model context search.<\/jats:p>","DOI":"10.1145\/2010324.1964929","type":"journal-article","created":{"date-parts":[[2011,7,26]],"date-time":"2011-07-26T14:17:46Z","timestamp":1311689866000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":121,"title":["Characterizing structural relationships in scenes using graph kernels"],"prefix":"10.1145","volume":"30","author":[{"given":"Matthew","family":"Fisher","sequence":"first","affiliation":[{"name":"Stanford University"}]},{"given":"Manolis","family":"Savva","sequence":"additional","affiliation":[{"name":"Stanford University"}]},{"given":"Pat","family":"Hanrahan","sequence":"additional","affiliation":[{"name":"Stanford University"}]}],"member":"320","published-online":{"date-parts":[[2011,7,25]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015424"},{"key":"e_1_2_2_2_1","doi-asserted-by":"crossref","unstructured":"Bao S. Sun M. and Savarese S. 2010. Toward coherent object detection and scene layout understanding. In CVPR 65--72.","DOI":"10.1109\/CVPR.2010.5540229"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bti1007"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1882261.1866205"},{"key":"e_1_2_2_5_1","doi-asserted-by":"crossref","unstructured":"Chen D. Tian X. Shen Y. and Ouhyoung M. 2003. On visual similarity based 3D model retrieval. In Computer graphics forum vol. 22 223--232.","DOI":"10.1111\/1467-8659.00669"},{"key":"e_1_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.5555\/345662"},{"key":"e_1_2_2_7_1","volume-title":"On in and on: An investigation into the linguistic encoding of spatial scenes. UMI","author":"Feist M.","unstructured":"Feist, M. 2000. On in and on: An investigation into the linguistic encoding of spatial scenes. UMI, Ann Arbor, Michigan."},{"key":"e_1_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1882261.1866204"},{"key":"e_1_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/588272.588279"},{"key":"e_1_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1015706.1015775"},{"key":"e_1_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/1576246.1531339"},{"key":"e_1_2_2_12_1","doi-asserted-by":"crossref","unstructured":"Galleguillos C. Rabinovich A. and Belongie S. 2008. Object categorization using co-occurrence location and appearance. In CVPR 1--8.","DOI":"10.1109\/CVPR.2008.4587799"},{"key":"e_1_2_2_13_1","volume-title":"Proceedings of the 16th Annual Conference on Learning Theory, 129--143","author":"Gartner T.","unstructured":"Gartner, T., Flach, P., and Wrobel, S. 2003. On graph kernels: Hardness results and efficient alternatives. In Proceedings of the 16th Annual Conference on Learning Theory, 129--143."},{"key":"e_1_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/1378889.1378950"},{"key":"e_1_2_2_15_1","doi-asserted-by":"publisher","unstructured":"Gupta A. Efros A. and Hebert M. 2010. Blocks world revisited: Image understanding using qualitative geometry and mechanics. Computer Vision--ECCV 482--496.","DOI":"10.5555\/1888089.1888126"},{"key":"e_1_2_2_16_1","doi-asserted-by":"publisher","unstructured":"Habegger B. and Debarbieux D. 2006. Integrating Data from the Web by Machine-Learning Tree-Pattern Queries. On the Move to Meaningful Internet Systems 941--948. 10.1007\/11914853_59","DOI":"10.1007\/11914853_59"},{"key":"e_1_2_2_17_1","doi-asserted-by":"crossref","unstructured":"Harchaoui Z. and Bach F. 2007. Image classification with segmentation graph kernels. In CVPR 1--8.","DOI":"10.1109\/CVPR.2007.383049"},{"key":"e_1_2_2_18_1","doi-asserted-by":"crossref","unstructured":"Kashima H. Tsuda K. and Inokuchi A. 2004. Kernels for graphs. Kernel methods in computational biology 155--170.","DOI":"10.7551\/mitpress\/4057.003.0010"},{"key":"e_1_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.68"},{"key":"e_1_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/1778765.1778840"},{"key":"e_1_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015446"},{"key":"e_1_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/1882261.1866203"},{"key":"e_1_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/781606.781639"},{"key":"e_1_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.3722\/cadaps.2008.753-763"},{"key":"e_1_2_2_25_1","unstructured":"Paraboschi L. Biasotti S. and Falcidieno B. 2007. 3D scene comparison using topological graphs. Eurographics Italian Chapter Trento (Italy) 87--93."},{"key":"e_1_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.5555\/299094.299105"},{"key":"e_1_2_2_27_1","volume-title":"1st International Workshop on Mining Graphs, Trees and Sequences, 65--74","author":"Ramon J.","unstructured":"Ramon, J., and G\u00e4rtner, T. 2003. Expressivity versus efficiency of graph kernels. In 1st International Workshop on Mining Graphs, Trees and Sequences, 65--74."},{"key":"e_1_2_2_28_1","doi-asserted-by":"crossref","unstructured":"Russell B. and Torralba A. 2009. Building a database of 3d scenes from user annotations. CVPR 2711--2718.","DOI":"10.1109\/CVPR.2009.5206643"},{"key":"e_1_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-007-0090-8"},{"key":"e_1_2_2_30_1","doi-asserted-by":"publisher","unstructured":"Salton G. and Buckley C. 1988. Term-weighting approaches in automatic text retrieval. In Information Processing and Management 513--523. 10.1016\/0306-4573(88)90021-0","DOI":"10.1016\/0306-4573(88)90021-0"},{"key":"e_1_2_2_31_1","doi-asserted-by":"publisher","unstructured":"Shawe-Taylor J. and Cristianini N. 2004. Kernel methods for pattern analysis. Cambridge University Press.","DOI":"10.5555\/975545"},{"key":"e_1_2_2_32_1","doi-asserted-by":"crossref","unstructured":"Shechtman E. and Irani M. 2007. Matching local self-similarities across images and videos. In CVPR 1--8.","DOI":"10.1109\/CVPR.2007.383198"},{"key":"e_1_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-007-0181-0"},{"key":"e_1_2_2_34_1","volume-title":"Proceedings of the 32nd Annual Conference of the Cognitive Science Society, 1--6.","author":"Xu Y.","unstructured":"Xu, Y., and Kemp, C. 2010. Constructing spatial concepts from universal primitives. Proceedings of the 32nd Annual Conference of the Cognitive Science Society, 1--6."}],"container-title":["ACM Transactions on Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2010324.1964929","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2010324.1964929","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T11:22:23Z","timestamp":1750245743000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2010324.1964929"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,7]]},"references-count":34,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2011,7]]}},"alternative-id":["10.1145\/2010324.1964929"],"URL":"https:\/\/doi.org\/10.1145\/2010324.1964929","relation":{},"ISSN":["0730-0301","1557-7368"],"issn-type":[{"value":"0730-0301","type":"print"},{"value":"1557-7368","type":"electronic"}],"subject":[],"published":{"date-parts":[[2011,7]]},"assertion":[{"value":"2011-07-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}