{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00242256","sets":["1164:4619:11919:11920"]},"path":["11920"],"owner":"44499","recid":"242256","title":["Incremental shape integration with inter-frame shape consistency using Neural SDF for a 3D Endoscopic system"],"pubdate":{"attribute_name":"公開日","attribute_value":"2025-01-14"},"_buckets":{"deposit":"5c7728b5-741a-4835-b15b-b3a773d2d025"},"_deposit":{"id":"242256","pid":{"type":"depid","value":"242256","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Incremental shape integration with inter-frame shape consistency using Neural SDF for a 3D Endoscopic system","author_link":["668696","668694","668691","668695","668693","668692"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Incremental shape integration with inter-frame shape consistency using Neural SDF for a 3D Endoscopic system"},{"subitem_title":"Incremental shape integration with inter-frame shape consistency using Neural SDF for a 3D Endoscopic system","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2025-01-14","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Kindai University"},{"subitem_text_value":"Kindai University"},{"subitem_text_value":"AIST"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Kindai University","subitem_text_language":"en"},{"subitem_text_value":"Kindai University","subitem_text_language":"en"},{"subitem_text_value":"AIST","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/242256/files/IPSJ-CVIM25240030.pdf","label":"IPSJ-CVIM25240030.pdf"},"date":[{"dateType":"Available","dateValue":"2027-01-14"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM25240030.pdf","filesize":[{"value":"33.2 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"59e9067b-2dab-473d-9818-191f07f98db2","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2025 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ryo, Furukawa"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroshi, Kawasaki"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Ryusuke, Sagawa"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ryo, Furukawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroshi, Kawasaki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Ryusuke, Sagawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8701","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"3D measurement for endoscopic systems has been largely demanded. One promising approach is to utilize active-stereo systems using a micro-sized pattern-projector attached to a head of a endoscope. Furthermore, a multi-frame integration is also desired to enlarge the reconstructed area. In this paper, we propose an incremental optimization technique of both the shape-field parameters and the positional parameters of the cameras and projectors. The method assumes that the input data is temporarily sequential images, i.e., endoscopic videos, and the relative positions between the camera and the projector may vary continuously. For solution, differential volume rendering algorithm conjunction with neural signed distance field (NeuralSDF) representation is proposed to simultaneously optimize the 3D scene and the camera/projector poses. Also, incremental optimization strategy where the optimized frames are gradually increased is proposed. In the experiment, the proposed method is evaluated by performing 3D reconstruction using both synthetic and real images, proving the effectiveness of our method.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"3D measurement for endoscopic systems has been largely demanded. One promising approach is to utilize active-stereo systems using a micro-sized pattern-projector attached to a head of a endoscope. Furthermore, a multi-frame integration is also desired to enlarge the reconstructed area. In this paper, we propose an incremental optimization technique of both the shape-field parameters and the positional parameters of the cameras and projectors. The method assumes that the input data is temporarily sequential images, i.e., endoscopic videos, and the relative positions between the camera and the projector may vary continuously. For solution, differential volume rendering algorithm conjunction with neural signed distance field (NeuralSDF) representation is proposed to simultaneously optimize the 3D scene and the camera/projector poses. Also, incremental optimization strategy where the optimized frames are gradually increased is proposed. In the experiment, the proposed method is evaluated by performing 3D reconstruction using both synthetic and real images, proving the effectiveness of our method.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2025-01-14","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"30","bibliographicVolumeNumber":"2025-CVIM-240"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T07:23:02.566245+00:00","created":"2025-01-19T01:47:21.320021+00:00","links":{},"id":242256}