{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/46588"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/46588","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Multicore construction of k-d trees with applications in graphics and vision","abstract":"The k-d tree is widely used in graphics and vision applications for accelerating retrieval from large sets of geometric entities in R^k. Despite speeding up an otherwise brute force search, the time to construct and traverse the k-d tree remain a bottleneck in many applications. Increasing parallelism in modern processors offers hope for further speedups. But while traversal is easily parallelized over a large number of queries, construction is not as easily parallelized and will become a serial bottleneck if left unparallelized. This thesis studies parallel k-d tree construction and its applications. The results are new multicore parallelizations of SAH k-d tree and FLANN k-d tree variants, and new ways of utilizing these parallelizations for accelerating object detection and scripting point algorithms.","abstract_html":"The k-d tree is widely used in graphics and vision applications for accelerating retrieval from large sets of geometric entities in R^k. Despite speeding up an otherwise brute force search, the time to construct and traverse the k-d tree remain a bottleneck in many applications. Increasing parallelism in modern processors offers hope for further speedups. But while traversal is easily parallelized over a large number of queries, construction is not as easily parallelized and will become a serial bottleneck if left unparallelized. This thesis studies parallel k-d tree construction and its applications. The results are new multicore parallelizations of SAH k-d tree and FLANN k-d tree variants, and new ways of utilizing these parallelizations for accelerating object detection and scripting point algorithms.","abstract_has_math":false,"creators":["Lu, Victor"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Hart, John C.","Forsyth, David A.","Hoiem, Derek W.","Stroila, Matei"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-01-16T17:55:16Z","date_published":"2014-01-16T17:55:16Z","updated_at":"2026-07-22T22:25:36Z","subjects":["vision","computer graphics","spatial data structures","k-d trees","multicore","parallel algorithms","ray-tracing","nearest neighbor search","image search","object detection","point cloud processing"],"languages":["en"],"rights":["Copyright 2013 Victor Lu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/46588","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hart, John C.","Forsyth, David A.","Hoiem, Derek W.","Stroila, Matei"]},{"key":"dc:creator","label":"Author","values":["Lu, Victor"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-01-16T17:55:16Z","2013-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["vision","computer graphics","spatial data structures","k-d trees","multicore","parallel algorithms","ray-tracing","nearest neighbor search","image search","object detection","point cloud processing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2013 Victor Lu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/46588"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The k-d tree is widely used in graphics and vision applications for accelerating retrieval from large sets of geometric entities in R^k. 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But while traversal is easily parallelized over a large number of queries, construction is not as easily parallelized and will become a serial bottleneck if left unparallelized. This thesis studies parallel k-d tree construction and its applications. The results are new multicore parallelizations of SAH k-d tree and FLANN k-d tree variants, and new ways of utilizing these parallelizations for accelerating object detection and scripting point algorithms.","Item withdrawn by Laura Spradlin (lspradl2@illinois.edu) on 2013-11-21T17:23:05Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Lu_Victor.pdf: 4681223 bytes, checksum: 28512effd9a0cb023c991ef48f5577d6 (MD5)","Made available in DSpace on 2014-01-16T17:55:16Z (GMT). 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