{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:U5DH23JXUW7P7BO446GOHCV6EU","short_pith_number":"pith:U5DH23JX","schema_version":"1.0","canonical_sha256":"a7467d6d37a5beff85dce78ce38abe251e4679f2bd30b36a23e58b08f3ed562c","source":{"kind":"arxiv","id":"2109.14828","version":1},"attestation_state":"computed","paper":{"title":"Uncertainty Estimation of Dense Optical-Flow for Robust Visual Navigation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Hongdong Li, JongHyuk Kim, Yonhon Ng","submitted_at":"2021-09-30T03:19:31Z","abstract_excerpt":"This paper presents a novel dense optical-flow algorithm to solve the monocular simultaneous localization and mapping (SLAM) problem for ground or aerial robots. Dense optical flow can effectively provide the ego-motion of the vehicle while enabling collision avoidance with the potential obstacles. Existing work has not fully utilized the uncertainty of the optical flow -- at most an isotropic Gaussian density model. We estimate the full uncertainty of the optical flow and propose a new eight-point algorithm based on the statistical Mahalanobis distance. Combined with the pose-graph optimizati"},"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":"2109.14828","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2021-09-30T03:19:31Z","cross_cats_sorted":[],"title_canon_sha256":"cdfbafcbcf91a6b1d20c7a57977114010ddfc15a248e3603f8ad755e6743a16e","abstract_canon_sha256":"2f581bd1d0b13e4c8e9331e15b73b77c7ab4745f2aa01c7542fc2963c179c41f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:18:44.784468Z","signature_b64":"EucSNhbHMuVDjYM49remAleeE2k8yywA2aOc5BpmII5cytXv3TYcRO/sdlB9l133gnsYKAnxDcGCFaqUezTjBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a7467d6d37a5beff85dce78ce38abe251e4679f2bd30b36a23e58b08f3ed562c","last_reissued_at":"2026-07-05T03:18:44.784079Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:18:44.784079Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Uncertainty Estimation of Dense Optical-Flow for Robust Visual Navigation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Hongdong Li, JongHyuk Kim, Yonhon Ng","submitted_at":"2021-09-30T03:19:31Z","abstract_excerpt":"This paper presents a novel dense optical-flow algorithm to solve the monocular simultaneous localization and mapping (SLAM) problem for ground or aerial robots. Dense optical flow can effectively provide the ego-motion of the vehicle while enabling collision avoidance with the potential obstacles. Existing work has not fully utilized the uncertainty of the optical flow -- at most an isotropic Gaussian density model. We estimate the full uncertainty of the optical flow and propose a new eight-point algorithm based on the statistical Mahalanobis distance. Combined with the pose-graph optimizati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.14828","kind":"arxiv","version":1},"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/2109.14828/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":"2109.14828","created_at":"2026-07-05T03:18:44.784141+00:00"},{"alias_kind":"arxiv_version","alias_value":"2109.14828v1","created_at":"2026-07-05T03:18:44.784141+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.14828","created_at":"2026-07-05T03:18:44.784141+00:00"},{"alias_kind":"pith_short_12","alias_value":"U5DH23JXUW7P","created_at":"2026-07-05T03:18:44.784141+00:00"},{"alias_kind":"pith_short_16","alias_value":"U5DH23JXUW7P7BO4","created_at":"2026-07-05T03:18:44.784141+00:00"},{"alias_kind":"pith_short_8","alias_value":"U5DH23JX","created_at":"2026-07-05T03:18:44.784141+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/U5DH23JXUW7P7BO446GOHCV6EU","json":"https://pith.science/pith/U5DH23JXUW7P7BO446GOHCV6EU.json","graph_json":"https://pith.science/api/pith-number/U5DH23JXUW7P7BO446GOHCV6EU/graph.json","events_json":"https://pith.science/api/pith-number/U5DH23JXUW7P7BO446GOHCV6EU/events.json","paper":"https://pith.science/paper/U5DH23JX"},"agent_actions":{"view_html":"https://pith.science/pith/U5DH23JXUW7P7BO446GOHCV6EU","download_json":"https://pith.science/pith/U5DH23JXUW7P7BO446GOHCV6EU.json","view_paper":"https://pith.science/paper/U5DH23JX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2109.14828&json=true","fetch_graph":"https://pith.science/api/pith-number/U5DH23JXUW7P7BO446GOHCV6EU/graph.json","fetch_events":"https://pith.science/api/pith-number/U5DH23JXUW7P7BO446GOHCV6EU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/U5DH23JXUW7P7BO446GOHCV6EU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/U5DH23JXUW7P7BO446GOHCV6EU/action/storage_attestation","attest_author":"https://pith.science/pith/U5DH23JXUW7P7BO446GOHCV6EU/action/author_attestation","sign_citation":"https://pith.science/pith/U5DH23JXUW7P7BO446GOHCV6EU/action/citation_signature","submit_replication":"https://pith.science/pith/U5DH23JXUW7P7BO446GOHCV6EU/action/replication_record"}},"created_at":"2026-07-05T03:18:44.784141+00:00","updated_at":"2026-07-05T03:18:44.784141+00:00"}