{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:PJDKHEDA7XKFVRA6VOTO6RRTGJ","short_pith_number":"pith:PJDKHEDA","canonical_record":{"source":{"id":"1808.03041","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-09T07:05:18Z","cross_cats_sorted":[],"title_canon_sha256":"7d6e88e9bb30ebecd2f1576583568d3d917e66c245f67fa4d9c88a3b8d08438f","abstract_canon_sha256":"e0c9cb62a0ed157f474cef29e61c71dd0618880981508259fa86c0107ab001e6"},"schema_version":"1.0"},"canonical_sha256":"7a46a39060fdd45ac41eaba6ef4633327d24338e0e289e6c22b827fd74a72633","source":{"kind":"arxiv","id":"1808.03041","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.03041","created_at":"2026-05-17T23:53:57Z"},{"alias_kind":"arxiv_version","alias_value":"1808.03041v4","created_at":"2026-05-17T23:53:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.03041","created_at":"2026-05-17T23:53:57Z"},{"alias_kind":"pith_short_12","alias_value":"PJDKHEDA7XKF","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"PJDKHEDA7XKFVRA6","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"PJDKHEDA","created_at":"2026-05-18T12:32:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:PJDKHEDA7XKFVRA6VOTO6RRTGJ","target":"record","payload":{"canonical_record":{"source":{"id":"1808.03041","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-09T07:05:18Z","cross_cats_sorted":[],"title_canon_sha256":"7d6e88e9bb30ebecd2f1576583568d3d917e66c245f67fa4d9c88a3b8d08438f","abstract_canon_sha256":"e0c9cb62a0ed157f474cef29e61c71dd0618880981508259fa86c0107ab001e6"},"schema_version":"1.0"},"canonical_sha256":"7a46a39060fdd45ac41eaba6ef4633327d24338e0e289e6c22b827fd74a72633","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:53:57.564710Z","signature_b64":"WtYQFe0M7GOSYnLjc03Hvqr0YUMPh+koMN/vugALkbK1WIVI9p6XDq7dacOpS+MamRfFQnFgGE3n2iZx+YFlAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7a46a39060fdd45ac41eaba6ef4633327d24338e0e289e6c22b827fd74a72633","last_reissued_at":"2026-05-17T23:53:57.564083Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:53:57.564083Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.03041","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:53:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"irUEK5YMlOBmJsLzatOytQFXLHvOx2Jaow2NlBZg/KvsMafngS8IXazTf53rmoSGSulWKfVczCN5EiWzKTV7Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T05:38:32.609097Z"},"content_sha256":"fe58a58820fe6861c2341e5a1202160907884bcebca232d8cff7da74164f5cbe","schema_version":"1.0","event_id":"sha256:fe58a58820fe6861c2341e5a1202160907884bcebca232d8cff7da74164f5cbe"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:PJDKHEDA7XKFVRA6VOTO6RRTGJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient Outlier Removal in Large Scale Global Structure-from-Motion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Danping Zou, Fei Wen, Peilin Liu, Rendong Ying","submitted_at":"2018-08-09T07:05:18Z","abstract_excerpt":"This work addresses the outlier removal problem in large-scale global structure-from-motion. In such applications, global outlier removal is very useful to mitigate the deterioration caused by mismatches in the feature point matching step. Unlike existing outlier removal methods, we exploit the structure in multiview geometry problems to propose a dimension reduced formulation, based on which two methods have been developed. The first method considers a convex relaxed $\\ell_1$ minimization and is solved by a single linear programming (LP), whilst the second one approximately solves the ideal $"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.03041","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:53:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fpiyYsYEFmhTYXJv44q7BGeK79vJwml7W3j1/14HQmYVRhLQha+S9fGACck+9I/pdcBVEfkHQHsfWCbvtuGUDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T05:38:32.609453Z"},"content_sha256":"2d84930dc47d735ef9bd92b137ccb4e8cd9f666b6ba4a1cc7d6a0eedd9ed944d","schema_version":"1.0","event_id":"sha256:2d84930dc47d735ef9bd92b137ccb4e8cd9f666b6ba4a1cc7d6a0eedd9ed944d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PJDKHEDA7XKFVRA6VOTO6RRTGJ/bundle.json","state_url":"https://pith.science/pith/PJDKHEDA7XKFVRA6VOTO6RRTGJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PJDKHEDA7XKFVRA6VOTO6RRTGJ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-24T05:38:32Z","links":{"resolver":"https://pith.science/pith/PJDKHEDA7XKFVRA6VOTO6RRTGJ","bundle":"https://pith.science/pith/PJDKHEDA7XKFVRA6VOTO6RRTGJ/bundle.json","state":"https://pith.science/pith/PJDKHEDA7XKFVRA6VOTO6RRTGJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PJDKHEDA7XKFVRA6VOTO6RRTGJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:PJDKHEDA7XKFVRA6VOTO6RRTGJ","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"e0c9cb62a0ed157f474cef29e61c71dd0618880981508259fa86c0107ab001e6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-09T07:05:18Z","title_canon_sha256":"7d6e88e9bb30ebecd2f1576583568d3d917e66c245f67fa4d9c88a3b8d08438f"},"schema_version":"1.0","source":{"id":"1808.03041","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.03041","created_at":"2026-05-17T23:53:57Z"},{"alias_kind":"arxiv_version","alias_value":"1808.03041v4","created_at":"2026-05-17T23:53:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.03041","created_at":"2026-05-17T23:53:57Z"},{"alias_kind":"pith_short_12","alias_value":"PJDKHEDA7XKF","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"PJDKHEDA7XKFVRA6","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"PJDKHEDA","created_at":"2026-05-18T12:32:43Z"}],"graph_snapshots":[{"event_id":"sha256:2d84930dc47d735ef9bd92b137ccb4e8cd9f666b6ba4a1cc7d6a0eedd9ed944d","target":"graph","created_at":"2026-05-17T23:53:57Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"This work addresses the outlier removal problem in large-scale global structure-from-motion. In such applications, global outlier removal is very useful to mitigate the deterioration caused by mismatches in the feature point matching step. Unlike existing outlier removal methods, we exploit the structure in multiview geometry problems to propose a dimension reduced formulation, based on which two methods have been developed. The first method considers a convex relaxed $\\ell_1$ minimization and is solved by a single linear programming (LP), whilst the second one approximately solves the ideal $","authors_text":"Danping Zou, Fei Wen, Peilin Liu, Rendong Ying","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-09T07:05:18Z","title":"Efficient Outlier Removal in Large Scale Global Structure-from-Motion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.03041","kind":"arxiv","version":4},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:fe58a58820fe6861c2341e5a1202160907884bcebca232d8cff7da74164f5cbe","target":"record","created_at":"2026-05-17T23:53:57Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"e0c9cb62a0ed157f474cef29e61c71dd0618880981508259fa86c0107ab001e6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-09T07:05:18Z","title_canon_sha256":"7d6e88e9bb30ebecd2f1576583568d3d917e66c245f67fa4d9c88a3b8d08438f"},"schema_version":"1.0","source":{"id":"1808.03041","kind":"arxiv","version":4}},"canonical_sha256":"7a46a39060fdd45ac41eaba6ef4633327d24338e0e289e6c22b827fd74a72633","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7a46a39060fdd45ac41eaba6ef4633327d24338e0e289e6c22b827fd74a72633","first_computed_at":"2026-05-17T23:53:57.564083Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:53:57.564083Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WtYQFe0M7GOSYnLjc03Hvqr0YUMPh+koMN/vugALkbK1WIVI9p6XDq7dacOpS+MamRfFQnFgGE3n2iZx+YFlAQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:53:57.564710Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.03041","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fe58a58820fe6861c2341e5a1202160907884bcebca232d8cff7da74164f5cbe","sha256:2d84930dc47d735ef9bd92b137ccb4e8cd9f666b6ba4a1cc7d6a0eedd9ed944d"],"state_sha256":"6e86081fb9cb5341190ca422dbb21e2555df8a7f2a9797caf35c3a2516ca7bf4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fYc5N68sBcvchZtsQnnaR73U8OkiP4ZEIjr6/91iTUSDXlUcxhv4Cd+9ntRtdPpyQawF55BT+/KVeRY2GBe7CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-24T05:38:32.611362Z","bundle_sha256":"436754cf97b87c587b554e91d2f9a532bf741d8f178b8fd8e1a1eb63ac830304"}}