{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:W7HGKLWGGLESSMLLDR3NJIWGEP","short_pith_number":"pith:W7HGKLWG","canonical_record":{"source":{"id":"1906.11182","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-26T16:02:44Z","cross_cats_sorted":[],"title_canon_sha256":"d2870f8ac7f731edadc230628844b1f6eeadf4edc59ece907454ef7118ed5dd3","abstract_canon_sha256":"15c4a2012b0b4a1d2f3a85b7d8b11a5443f357cfa1c813efd58e2227cbc63c7c"},"schema_version":"1.0"},"canonical_sha256":"b7ce652ec632c929316b1c76d4a2c623c8278e76cc9fec659f7b1339371f023b","source":{"kind":"arxiv","id":"1906.11182","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.11182","created_at":"2026-05-17T23:42:09Z"},{"alias_kind":"arxiv_version","alias_value":"1906.11182v1","created_at":"2026-05-17T23:42:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.11182","created_at":"2026-05-17T23:42:09Z"},{"alias_kind":"pith_short_12","alias_value":"W7HGKLWGGLES","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"W7HGKLWGGLESSMLL","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"W7HGKLWG","created_at":"2026-05-18T12:33:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:W7HGKLWGGLESSMLLDR3NJIWGEP","target":"record","payload":{"canonical_record":{"source":{"id":"1906.11182","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-26T16:02:44Z","cross_cats_sorted":[],"title_canon_sha256":"d2870f8ac7f731edadc230628844b1f6eeadf4edc59ece907454ef7118ed5dd3","abstract_canon_sha256":"15c4a2012b0b4a1d2f3a85b7d8b11a5443f357cfa1c813efd58e2227cbc63c7c"},"schema_version":"1.0"},"canonical_sha256":"b7ce652ec632c929316b1c76d4a2c623c8278e76cc9fec659f7b1339371f023b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:09.552292Z","signature_b64":"qnqnQXTIzLa+msnoYN2OT+Zvzg3oyw1a0Gdzt7ooJRV35gTtcSZnRt+J8sUYzmgJaZsbQnyVMo9LEhSM+ck1Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7ce652ec632c929316b1c76d4a2c623c8278e76cc9fec659f7b1339371f023b","last_reissued_at":"2026-05-17T23:42:09.551631Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:09.551631Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.11182","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:42:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2qeGv6y/7PasS/xxf/k6nL0I6iICxb757zxvOovsnicSf4uUDXbT3LJM+MS4mKPu23iz8u6lRPc9Vg4jLkreDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T17:13:41.216598Z"},"content_sha256":"fd0dd574de37ea1fa5a674424ad20cb3d870cdff37c204c2f30b3d4bc7c9db1b","schema_version":"1.0","event_id":"sha256:fd0dd574de37ea1fa5a674424ad20cb3d870cdff37c204c2f30b3d4bc7c9db1b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:W7HGKLWGGLESSMLLDR3NJIWGEP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian Inference of Spacecraft Pose using Particle Filtering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Brien Flewelling, Joseph Mundy, Manoranjan Majji, Maxim Bazik","submitted_at":"2019-06-26T16:02:44Z","abstract_excerpt":"Automated 3D pose estimation of satellites and other known space objects is a critical component of space situational awareness. Ground-based imagery offers a convenient data source for satellite characterization; however, analysis algorithms must contend with atmospheric distortion, variable lighting, and unknown reflectance properties. Traditional feature-based pose estimation approaches are unable to discover an accurate correlation between a known 3D model and imagery given this challenging image environment. This paper presents an innovative method for automated 3D pose estimation of know"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.11182","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":""},"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":"2026-05-17T23:42:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+XjKn2t5/ofpTh/SfZB6PHHjnkZV7+bVEWGmcYiZSRHOXKAGQyvodThAkfEUC6NzlztbB3Qqq2SRBDhc0QGOBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T17:13:41.216954Z"},"content_sha256":"fafbd93b99a391c7cd181317efd31a756cc3951ab9dd7d619088b8d8cf265dce","schema_version":"1.0","event_id":"sha256:fafbd93b99a391c7cd181317efd31a756cc3951ab9dd7d619088b8d8cf265dce"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W7HGKLWGGLESSMLLDR3NJIWGEP/bundle.json","state_url":"https://pith.science/pith/W7HGKLWGGLESSMLLDR3NJIWGEP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W7HGKLWGGLESSMLLDR3NJIWGEP/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":"2026-06-26T17:13:41Z","links":{"resolver":"https://pith.science/pith/W7HGKLWGGLESSMLLDR3NJIWGEP","bundle":"https://pith.science/pith/W7HGKLWGGLESSMLLDR3NJIWGEP/bundle.json","state":"https://pith.science/pith/W7HGKLWGGLESSMLLDR3NJIWGEP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W7HGKLWGGLESSMLLDR3NJIWGEP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:W7HGKLWGGLESSMLLDR3NJIWGEP","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":"15c4a2012b0b4a1d2f3a85b7d8b11a5443f357cfa1c813efd58e2227cbc63c7c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-26T16:02:44Z","title_canon_sha256":"d2870f8ac7f731edadc230628844b1f6eeadf4edc59ece907454ef7118ed5dd3"},"schema_version":"1.0","source":{"id":"1906.11182","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.11182","created_at":"2026-05-17T23:42:09Z"},{"alias_kind":"arxiv_version","alias_value":"1906.11182v1","created_at":"2026-05-17T23:42:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.11182","created_at":"2026-05-17T23:42:09Z"},{"alias_kind":"pith_short_12","alias_value":"W7HGKLWGGLES","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"W7HGKLWGGLESSMLL","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"W7HGKLWG","created_at":"2026-05-18T12:33:30Z"}],"graph_snapshots":[{"event_id":"sha256:fafbd93b99a391c7cd181317efd31a756cc3951ab9dd7d619088b8d8cf265dce","target":"graph","created_at":"2026-05-17T23:42:09Z","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":"Automated 3D pose estimation of satellites and other known space objects is a critical component of space situational awareness. Ground-based imagery offers a convenient data source for satellite characterization; however, analysis algorithms must contend with atmospheric distortion, variable lighting, and unknown reflectance properties. Traditional feature-based pose estimation approaches are unable to discover an accurate correlation between a known 3D model and imagery given this challenging image environment. This paper presents an innovative method for automated 3D pose estimation of know","authors_text":"Brien Flewelling, Joseph Mundy, Manoranjan Majji, Maxim Bazik","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-26T16:02:44Z","title":"Bayesian Inference of Spacecraft Pose using Particle Filtering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.11182","kind":"arxiv","version":1},"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:fd0dd574de37ea1fa5a674424ad20cb3d870cdff37c204c2f30b3d4bc7c9db1b","target":"record","created_at":"2026-05-17T23:42:09Z","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":"15c4a2012b0b4a1d2f3a85b7d8b11a5443f357cfa1c813efd58e2227cbc63c7c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-26T16:02:44Z","title_canon_sha256":"d2870f8ac7f731edadc230628844b1f6eeadf4edc59ece907454ef7118ed5dd3"},"schema_version":"1.0","source":{"id":"1906.11182","kind":"arxiv","version":1}},"canonical_sha256":"b7ce652ec632c929316b1c76d4a2c623c8278e76cc9fec659f7b1339371f023b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7ce652ec632c929316b1c76d4a2c623c8278e76cc9fec659f7b1339371f023b","first_computed_at":"2026-05-17T23:42:09.551631Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:42:09.551631Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qnqnQXTIzLa+msnoYN2OT+Zvzg3oyw1a0Gdzt7ooJRV35gTtcSZnRt+J8sUYzmgJaZsbQnyVMo9LEhSM+ck1Bg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:42:09.552292Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.11182","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fd0dd574de37ea1fa5a674424ad20cb3d870cdff37c204c2f30b3d4bc7c9db1b","sha256:fafbd93b99a391c7cd181317efd31a756cc3951ab9dd7d619088b8d8cf265dce"],"state_sha256":"86eec015a7a7c157eda2636c690fca1e9de8bc7c249605b49937c13052033c01"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UH+X7w5DcG1jT5seDsiTOAOLeAmSUGxnDBqP5Hnd6Lo8/rP7Y41gGOHNg8WUnLCTU2+7bpad2dgxqFJi3ROuBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-26T17:13:41.219157Z","bundle_sha256":"31240467544b0538fe3f982505d60ed146284ca28f403e36adb862dfdbba44ff"}}