{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:N637HGXZLA22UVH4HT6UGSS66T","short_pith_number":"pith:N637HGXZ","canonical_record":{"source":{"id":"1611.06011","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-18T09:00:22Z","cross_cats_sorted":[],"title_canon_sha256":"108a80fc88c38acf6db54b34bf70fbe5774ca0af0a42b1da5a0e8450dde0bcc1","abstract_canon_sha256":"6a6aea22cbea9bebc58b9026d047a070056e5f47d4ee20c95b85517b8b4c6acf"},"schema_version":"1.0"},"canonical_sha256":"6fb7f39af95835aa54fc3cfd434a5ef4ea952f820cbac4351232dfd0b697b3dc","source":{"kind":"arxiv","id":"1611.06011","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.06011","created_at":"2026-05-18T00:38:39Z"},{"alias_kind":"arxiv_version","alias_value":"1611.06011v2","created_at":"2026-05-18T00:38:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.06011","created_at":"2026-05-18T00:38:39Z"},{"alias_kind":"pith_short_12","alias_value":"N637HGXZLA22","created_at":"2026-05-18T12:30:32Z"},{"alias_kind":"pith_short_16","alias_value":"N637HGXZLA22UVH4","created_at":"2026-05-18T12:30:32Z"},{"alias_kind":"pith_short_8","alias_value":"N637HGXZ","created_at":"2026-05-18T12:30:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:N637HGXZLA22UVH4HT6UGSS66T","target":"record","payload":{"canonical_record":{"source":{"id":"1611.06011","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-18T09:00:22Z","cross_cats_sorted":[],"title_canon_sha256":"108a80fc88c38acf6db54b34bf70fbe5774ca0af0a42b1da5a0e8450dde0bcc1","abstract_canon_sha256":"6a6aea22cbea9bebc58b9026d047a070056e5f47d4ee20c95b85517b8b4c6acf"},"schema_version":"1.0"},"canonical_sha256":"6fb7f39af95835aa54fc3cfd434a5ef4ea952f820cbac4351232dfd0b697b3dc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:38:39.833110Z","signature_b64":"eget8D1ZLmXGsyavjjbg/Ihm3l34qG6PGuQkl4qDWNonOUnvy8oE75ExRYja+N0qGsPBn0xlb+OBZ/RW6OJjCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6fb7f39af95835aa54fc3cfd434a5ef4ea952f820cbac4351232dfd0b697b3dc","last_reissued_at":"2026-05-18T00:38:39.832725Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:38:39.832725Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1611.06011","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:38:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7EvJYIRQomjc8ReNcs7Q+3KOIf2EKCn+3t+he2SZtZbiqXKGb9KAVuG9BWNlM/FmnLI431XtvrtpsRxkMUVwAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T00:12:45.003359Z"},"content_sha256":"03de6fe2d7215ee6fdd2bfa006c441ce88fc4f504b3b314882c1b2ad4b93a00c","schema_version":"1.0","event_id":"sha256:03de6fe2d7215ee6fdd2bfa006c441ce88fc4f504b3b314882c1b2ad4b93a00c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:N637HGXZLA22UVH4HT6UGSS66T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Online Visual Multi-Object Tracking via Labeled Random Finite Set Filtering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ba-Ngu Vo, Ba-Tuong Vo, Du Yong Kim","submitted_at":"2016-11-18T09:00:22Z","abstract_excerpt":"This paper proposes an online visual multi-object tracking algorithm using a top-down Bayesian formulation that seamlessly integrates state estimation, track management, clutter rejection, occlusion and mis-detection handling into a single recursion. This is achieved by modeling the multi-object state as labeled random finite set and using the Bayes recursion to propagate the multi-object filtering density forward in time. The proposed filter updates tracks with detections but switches to image data when mis-detection occurs, thereby exploiting the efficiency of detection data and the accuracy"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.06011","kind":"arxiv","version":2},"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":"2026-05-18T00:38:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tqHM1ry19j4Jrbqoh4pknWudTpfXUyFCz6bKf5mIJQ43DqG50ojKKqy8KK8XaB0MZkVZI1X8IsHbpQYg7uq5BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T00:12:45.003699Z"},"content_sha256":"b7d7099d9ec21dd75395fc4761fc27a28100d22454e4f3fc84ccd3d4a028e7d1","schema_version":"1.0","event_id":"sha256:b7d7099d9ec21dd75395fc4761fc27a28100d22454e4f3fc84ccd3d4a028e7d1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N637HGXZLA22UVH4HT6UGSS66T/bundle.json","state_url":"https://pith.science/pith/N637HGXZLA22UVH4HT6UGSS66T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N637HGXZLA22UVH4HT6UGSS66T/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":"2026-06-27T00:12:45Z","links":{"resolver":"https://pith.science/pith/N637HGXZLA22UVH4HT6UGSS66T","bundle":"https://pith.science/pith/N637HGXZLA22UVH4HT6UGSS66T/bundle.json","state":"https://pith.science/pith/N637HGXZLA22UVH4HT6UGSS66T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N637HGXZLA22UVH4HT6UGSS66T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:N637HGXZLA22UVH4HT6UGSS66T","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":"6a6aea22cbea9bebc58b9026d047a070056e5f47d4ee20c95b85517b8b4c6acf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-18T09:00:22Z","title_canon_sha256":"108a80fc88c38acf6db54b34bf70fbe5774ca0af0a42b1da5a0e8450dde0bcc1"},"schema_version":"1.0","source":{"id":"1611.06011","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.06011","created_at":"2026-05-18T00:38:39Z"},{"alias_kind":"arxiv_version","alias_value":"1611.06011v2","created_at":"2026-05-18T00:38:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.06011","created_at":"2026-05-18T00:38:39Z"},{"alias_kind":"pith_short_12","alias_value":"N637HGXZLA22","created_at":"2026-05-18T12:30:32Z"},{"alias_kind":"pith_short_16","alias_value":"N637HGXZLA22UVH4","created_at":"2026-05-18T12:30:32Z"},{"alias_kind":"pith_short_8","alias_value":"N637HGXZ","created_at":"2026-05-18T12:30:32Z"}],"graph_snapshots":[{"event_id":"sha256:b7d7099d9ec21dd75395fc4761fc27a28100d22454e4f3fc84ccd3d4a028e7d1","target":"graph","created_at":"2026-05-18T00:38:39Z","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 paper proposes an online visual multi-object tracking algorithm using a top-down Bayesian formulation that seamlessly integrates state estimation, track management, clutter rejection, occlusion and mis-detection handling into a single recursion. This is achieved by modeling the multi-object state as labeled random finite set and using the Bayes recursion to propagate the multi-object filtering density forward in time. The proposed filter updates tracks with detections but switches to image data when mis-detection occurs, thereby exploiting the efficiency of detection data and the accuracy","authors_text":"Ba-Ngu Vo, Ba-Tuong Vo, Du Yong Kim","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-18T09:00:22Z","title":"Online Visual Multi-Object Tracking via Labeled Random Finite Set Filtering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.06011","kind":"arxiv","version":2},"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":"sha256:03de6fe2d7215ee6fdd2bfa006c441ce88fc4f504b3b314882c1b2ad4b93a00c","target":"record","created_at":"2026-05-18T00:38:39Z","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":"6a6aea22cbea9bebc58b9026d047a070056e5f47d4ee20c95b85517b8b4c6acf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-18T09:00:22Z","title_canon_sha256":"108a80fc88c38acf6db54b34bf70fbe5774ca0af0a42b1da5a0e8450dde0bcc1"},"schema_version":"1.0","source":{"id":"1611.06011","kind":"arxiv","version":2}},"canonical_sha256":"6fb7f39af95835aa54fc3cfd434a5ef4ea952f820cbac4351232dfd0b697b3dc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6fb7f39af95835aa54fc3cfd434a5ef4ea952f820cbac4351232dfd0b697b3dc","first_computed_at":"2026-05-18T00:38:39.832725Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:38:39.832725Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eget8D1ZLmXGsyavjjbg/Ihm3l34qG6PGuQkl4qDWNonOUnvy8oE75ExRYja+N0qGsPBn0xlb+OBZ/RW6OJjCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:38:39.833110Z","signed_message":"canonical_sha256_bytes"},"source_id":"1611.06011","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:03de6fe2d7215ee6fdd2bfa006c441ce88fc4f504b3b314882c1b2ad4b93a00c","sha256:b7d7099d9ec21dd75395fc4761fc27a28100d22454e4f3fc84ccd3d4a028e7d1"],"state_sha256":"ca2d8e6b807865450f8c183fdabd6ef46469c4ea12e671f59e39bad1cbd0f50c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8ze2Sj5pL4ufkc1zf1U6FAvSJJvCcqiqs37yFxFcWdFRVmJSnlS+qaPny6jBZZS4YppWc1RbDk3KVlHkJFEiCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T00:12:45.005513Z","bundle_sha256":"cfa1f948d1284f5db027047de10b2e6da01e30c20453813d3c79501c045e9a41"}}