{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/44195"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/44195","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Predicting object occupancy on the floor from RGBD images of indoor scenes","abstract":"This thesis presents an approach to predict the occupied area on the floor in an image of an indoor scene. The goal is to be able to obtain navigable areas even in cluttered indoor environments. This algorithm could be used in the field of robotics where robots need to navigate through a room while being mindful of the surrounding objects. The results are quite close to the ground truth, as exemplified by the false positive, false negative, precision and recall rates. Using this algorithm improves the label predictions.","abstract_html":"This thesis presents an approach to predict the occupied area on the floor in an image of an indoor scene. The goal is to be able to obtain navigable areas even in cluttered indoor environments. This algorithm could be used in the field of robotics where robots need to navigate through a room while being mindful of the surrounding objects. The results are quite close to the ground truth, as exemplified by the false positive, false negative, precision and recall rates. Using this algorithm improves the label predictions.","abstract_has_math":false,"creators":["Bhobe, Sujay"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Hoiem, Derek W."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-05-24T21:53:54Z","date_published":"2013-05-24T21:53:54Z","updated_at":"2026-07-22T22:25:33Z","subjects":["object occupancy","graph cuts","alpha expansion","label prediction","overhead view","scene understanding","computer vision"],"languages":["en"],"rights":["Copyright 2013 Sujay Uday Bhobe"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/44195","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hoiem, Derek W."]},{"key":"dc:creator","label":"Author","values":["Bhobe, Sujay"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2013-05-24T21:53:54Z","2013-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"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":["object occupancy","graph cuts","alpha expansion","label prediction","overhead view","scene understanding","computer vision"]}]},{"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 Sujay Uday Bhobe"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/44195"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This thesis presents an approach to predict the occupied area on the floor in an image of an indoor scene. The goal is to be able to obtain navigable areas even in cluttered indoor environments. This algorithm could be used in the field of robotics where robots need to navigate through a room while being mindful of the surrounding objects. The results are quite close to the ground truth, as exemplified by the false positive, false negative, precision and recall rates. Using this algorithm improves the label predictions.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2013-04-22T17:57:56Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 Bhobe_Sujay_MS_Thesis.zip: 22828 bytes, checksum: f3c60303f9f6b4e5470a982c25e94adb (MD5) Bhobe_Sujay.pdf: 1521794 bytes, checksum: 713917eb99051349c24aab6a07993165 (MD5)","Made available in DSpace on 2013-05-24T21:53:54Z (GMT). No. of bitstreams: 3 Sujay_Bhobe.pdf: 1521794 bytes, checksum: 713917eb99051349c24aab6a07993165 (MD5) Bhobe_Sujay_MSThesis_Files.zip: 24039 bytes, checksum: dcc264e5be236f22d5f6cba88d668a01 (MD5) license.txt: 4060 bytes, checksum: 6c16f827620e19456b74867ebc939654 (MD5)"]},{"key":"dc:title","label":"Title","values":["Predicting object occupancy on the floor from RGBD images of indoor scenes"]}]}],"canonical_facts":{"dc:contributor":["Hoiem, Derek W."],"dc:creator":["Bhobe, Sujay"],"dc:date":["2013-05-24T21:53:54Z","2013-05"],"dc:description":["This thesis presents an approach to predict the occupied area on the floor in an image of an indoor scene. The goal is to be able to obtain navigable areas even in cluttered indoor environments. This algorithm could be used in the field of robotics where robots need to navigate through a room while being mindful of the surrounding objects. The results are quite close to the ground truth, as exemplified by the false positive, false negative, precision and recall rates. Using this algorithm improves the label predictions.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2013-04-22T17:57:56Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 Bhobe_Sujay_MS_Thesis.zip: 22828 bytes, checksum: f3c60303f9f6b4e5470a982c25e94adb (MD5) Bhobe_Sujay.pdf: 1521794 bytes, checksum: 713917eb99051349c24aab6a07993165 (MD5)","Made available in DSpace on 2013-05-24T21:53:54Z (GMT). No. of bitstreams: 3 Sujay_Bhobe.pdf: 1521794 bytes, checksum: 713917eb99051349c24aab6a07993165 (MD5) Bhobe_Sujay_MSThesis_Files.zip: 24039 bytes, checksum: dcc264e5be236f22d5f6cba88d668a01 (MD5) license.txt: 4060 bytes, checksum: 6c16f827620e19456b74867ebc939654 (MD5)"],"dc:identifier":["http://hdl.handle.net/2142/44195"],"dc:language":["en"],"dc:rights":["Copyright 2013 Sujay Uday Bhobe"],"dc:subject":["object occupancy","graph cuts","alpha expansion","label prediction","overhead view","scene understanding","computer vision"],"dc:title":["Predicting object occupancy on the floor from RGBD images of indoor scenes"],"dc:type":["text"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:33Z"}