{"_buckets": {"deposit": "20160068-1001-4596-8fcb-0f6c2a46b330"}, "_deposit": {"id": "51800", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "51800"}, "status": "published"}, "_oai": {"id": "oai:tsukuba.repo.nii.ac.jp:00051800"}, "item_5_biblio_info_6": {"attribute_name": "\u66f8\u8a8c\u60c5\u5831", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2018-07", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "42046", "bibliographicPageStart": "42030", "bibliographicVolumeNumber": "6", "bibliographic_titles": [{"bibliographic_title": "IEEE Access"}]}]}, "item_5_description_4": {"attribute_name": "\u6284\u9332", "attribute_value_mlt": [{"subitem_description": "Real-time stereo vision is attractive in many areas such as outdoor mapping and navigation. As a popular accelerator in the image processing field, GPU is widely used for the studies of the stereo vision algorithms. Recently, many stereo vision systems on GPU have achieved low error rate, as a result of the development of deep learning. However, their processing speed is normally far from the real-time requirement. In this paper, we propose a real-time stereo vision system on GPU for the high-resolution images. This system also maintains a low error rate compared with other fast systems. In our approach, the image is resized to reduce the computational complexity and to realize the real-time processing. The low error rate is kept by using the cost aggregation with multiple blocks, secondary matching and sub-pixel estimation. Its processing speed is 41 fps for 2888\u00d71920 pixels images when the maximum disparity is 760.", "subitem_description_type": "Abstract"}]}, "item_5_publisher_27": {"attribute_name": "\u51fa\u7248\u8005", "attribute_value_mlt": [{"subitem_publisher": "IEEE"}]}, "item_5_relation_11": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type_id": {"subitem_relation_type_id_text": "10.1109/ACCESS.2018.2859445", "subitem_relation_type_select": "DOI"}}]}, "item_5_rights_12": {"attribute_name": "\u6a29\u5229", "attribute_value_mlt": [{"subitem_rights": "This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/"}]}, "item_5_select_15": {"attribute_name": "\u8457\u8005\u7248\u30d5\u30e9\u30b0", "attribute_value_mlt": [{"subitem_select_item": "publisher"}]}, "item_5_source_id_7": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "2169-3536", "subitem_source_identifier_type": "ISSN"}]}, "item_creator": {"attribute_name": "\u8457\u8005", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "\u4e38\u5c71, \u52c9"}, {"creatorName": "\u30de\u30eb\u30e4\u30de, \u30c4\u30c8\u30e0", "creatorNameLang": "ja-Kana"}, {"creatorName": "MARUYAMA, Tsutomu", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "204876", "nameIdentifierScheme": "WEKO"}, {"nameIdentifier": "00292532", "nameIdentifierScheme": "e-Rad", "nameIdentifierURI": "https://nrid.nii.ac.jp/ja/nrid/1000000292532"}, {"nameIdentifier": "0000001009", "nameIdentifierScheme": "\u7b51\u6ce2\u5927\u5b66\u7814\u7a76\u8005\u7dcf\u89a7", "nameIdentifierURI": "http://trios.tsukuba.ac.jp/researcher/0000001009"}]}, {"creatorNames": [{"creatorName": "Chang, Qiong", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "213014", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "\u30d5\u30a1\u30a4\u30eb\u60c5\u5831", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2019-07-29"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "IEEE Access_6-42030.pdf", "filesize": [{"value": "3.6 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_6", "mimetype": "application/pdf", "size": 3600000.0, "url": {"label": "IEEE Access_6-42030", "url": "https://tsukuba.repo.nii.ac.jp/record/51800/files/IEEE Access_6-42030.pdf"}, "version_id": "5bf187c0-0d60-45a7-88f5-4a013768d100"}]}, "item_language": {"attribute_name": "\u8a00\u8a9e", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "\u8cc7\u6e90\u30bf\u30a4\u30d7", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "Real-Time Stereo Vision System: A Multi-Block Matching on GPU", "item_titles": {"attribute_name": "\u30bf\u30a4\u30c8\u30eb", "attribute_value_mlt": [{"subitem_title": "Real-Time Stereo Vision System: A Multi-Block Matching on GPU"}]}, "item_type_id": "5", "owner": "1", "path": ["152/1233", "3/62/5591/7554"], "permalink_uri": "http://hdl.handle.net/2241/00157229", "pubdate": {"attribute_name": "\u516c\u958b\u65e5", "attribute_value": "2019-07-29"}, "publish_date": "2019-07-29", "publish_status": "0", "recid": "51800", "relation": {}, "relation_version_is_last": true, "title": ["Real-Time Stereo Vision System: A Multi-Block Matching on GPU"], "weko_shared_id": 5}