{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:2D3VDBH27VYCA3MFOGNLG6ONPL","short_pith_number":"pith:2D3VDBH2","schema_version":"1.0","canonical_sha256":"d0f75184fafd70206d85719ab379cd7ae62e84c8797f494492aaa15770b29343","source":{"kind":"arxiv","id":"2310.15072","version":3},"attestation_state":"computed","paper":{"title":"RD-VIO: Robust Visual-Inertial Odometry for Mobile Augmented Reality in Dynamic Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Gan Huang, Guofeng Zhang, Hujun Bao, Jinyu Li, Nan Wang, Xiaokun Pan, Ziyang Zhang","submitted_at":"2023-10-23T16:30:39Z","abstract_excerpt":"It is typically challenging for visual or visual-inertial odometry systems to handle the problems of dynamic scenes and pure rotation. In this work, we design a novel visual-inertial odometry (VIO) system called RD-VIO to handle both of these two problems. Firstly, we propose an IMU-PARSAC algorithm which can robustly detect and match keypoints in a two-stage process. In the first state, landmarks are matched with new keypoints using visual and IMU measurements. We collect statistical information from the matching and then guide the intra-keypoint matching in the second stage. Secondly, to han"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2310.15072","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2023-10-23T16:30:39Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"acdc6de90e9aeb8d1f74cda12051b0e7efda4f1d20cd02965fad4a2f841c7ed8","abstract_canon_sha256":"7e5eaa82a11c7b76ffded06f34acc5d0d4298d9d217220702eb6832ac7c13f8e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:45:49.855050Z","signature_b64":"wwyOyewxju2jf2mg8OtIoW7pnSfZR5RV0kprVXYx/oewVpBc3jICNWLqTNP7Bflb9M+vRwuwgW7G9Q5YP1rkBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d0f75184fafd70206d85719ab379cd7ae62e84c8797f494492aaa15770b29343","last_reissued_at":"2026-07-05T07:45:49.854478Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:45:49.854478Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"RD-VIO: Robust Visual-Inertial Odometry for Mobile Augmented Reality in Dynamic Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Gan Huang, Guofeng Zhang, Hujun Bao, Jinyu Li, Nan Wang, Xiaokun Pan, Ziyang Zhang","submitted_at":"2023-10-23T16:30:39Z","abstract_excerpt":"It is typically challenging for visual or visual-inertial odometry systems to handle the problems of dynamic scenes and pure rotation. In this work, we design a novel visual-inertial odometry (VIO) system called RD-VIO to handle both of these two problems. Firstly, we propose an IMU-PARSAC algorithm which can robustly detect and match keypoints in a two-stage process. In the first state, landmarks are matched with new keypoints using visual and IMU measurements. We collect statistical information from the matching and then guide the intra-keypoint matching in the second stage. Secondly, to han"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.15072","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2310.15072/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2310.15072","created_at":"2026-07-05T07:45:49.854547+00:00"},{"alias_kind":"arxiv_version","alias_value":"2310.15072v3","created_at":"2026-07-05T07:45:49.854547+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.15072","created_at":"2026-07-05T07:45:49.854547+00:00"},{"alias_kind":"pith_short_12","alias_value":"2D3VDBH27VYC","created_at":"2026-07-05T07:45:49.854547+00:00"},{"alias_kind":"pith_short_16","alias_value":"2D3VDBH27VYCA3MF","created_at":"2026-07-05T07:45:49.854547+00:00"},{"alias_kind":"pith_short_8","alias_value":"2D3VDBH2","created_at":"2026-07-05T07:45:49.854547+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2D3VDBH27VYCA3MFOGNLG6ONPL","json":"https://pith.science/pith/2D3VDBH27VYCA3MFOGNLG6ONPL.json","graph_json":"https://pith.science/api/pith-number/2D3VDBH27VYCA3MFOGNLG6ONPL/graph.json","events_json":"https://pith.science/api/pith-number/2D3VDBH27VYCA3MFOGNLG6ONPL/events.json","paper":"https://pith.science/paper/2D3VDBH2"},"agent_actions":{"view_html":"https://pith.science/pith/2D3VDBH27VYCA3MFOGNLG6ONPL","download_json":"https://pith.science/pith/2D3VDBH27VYCA3MFOGNLG6ONPL.json","view_paper":"https://pith.science/paper/2D3VDBH2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2310.15072&json=true","fetch_graph":"https://pith.science/api/pith-number/2D3VDBH27VYCA3MFOGNLG6ONPL/graph.json","fetch_events":"https://pith.science/api/pith-number/2D3VDBH27VYCA3MFOGNLG6ONPL/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2D3VDBH27VYCA3MFOGNLG6ONPL/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2D3VDBH27VYCA3MFOGNLG6ONPL/action/storage_attestation","attest_author":"https://pith.science/pith/2D3VDBH27VYCA3MFOGNLG6ONPL/action/author_attestation","sign_citation":"https://pith.science/pith/2D3VDBH27VYCA3MFOGNLG6ONPL/action/citation_signature","submit_replication":"https://pith.science/pith/2D3VDBH27VYCA3MFOGNLG6ONPL/action/replication_record"}},"created_at":"2026-07-05T07:45:49.854547+00:00","updated_at":"2026-07-05T07:45:49.854547+00:00"}