{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:B32TIWB4R2PVT2R27BA6DU4K7Z","short_pith_number":"pith:B32TIWB4","canonical_record":{"source":{"id":"1902.10016","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-26T15:56:27Z","cross_cats_sorted":[],"title_canon_sha256":"d53cb22880a171a3784e506dbbcb16ad58965738b616d087dcd1a84b963c3b36","abstract_canon_sha256":"620c350f95349f7b5b12dc72842cb41704cacc69edb173dc766f0aabd6369a86"},"schema_version":"1.0"},"canonical_sha256":"0ef534583c8e9f59ea3af841e1d38afe565a4db030e02f5982bd5cb876244fdb","source":{"kind":"arxiv","id":"1902.10016","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.10016","created_at":"2026-05-17T23:52:34Z"},{"alias_kind":"arxiv_version","alias_value":"1902.10016v1","created_at":"2026-05-17T23:52:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.10016","created_at":"2026-05-17T23:52:34Z"},{"alias_kind":"pith_short_12","alias_value":"B32TIWB4R2PV","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"B32TIWB4R2PVT2R2","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"B32TIWB4","created_at":"2026-05-18T12:33:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:B32TIWB4R2PVT2R27BA6DU4K7Z","target":"record","payload":{"canonical_record":{"source":{"id":"1902.10016","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-26T15:56:27Z","cross_cats_sorted":[],"title_canon_sha256":"d53cb22880a171a3784e506dbbcb16ad58965738b616d087dcd1a84b963c3b36","abstract_canon_sha256":"620c350f95349f7b5b12dc72842cb41704cacc69edb173dc766f0aabd6369a86"},"schema_version":"1.0"},"canonical_sha256":"0ef534583c8e9f59ea3af841e1d38afe565a4db030e02f5982bd5cb876244fdb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:52:34.862891Z","signature_b64":"R+p/WuDdVgJZzNCxcR9G1CG928wCw36jXPpUs1P2uEH7+EpRSPYIFMadW8zbLDOkpGhIdgZxWjVkIwvPT3huCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0ef534583c8e9f59ea3af841e1d38afe565a4db030e02f5982bd5cb876244fdb","last_reissued_at":"2026-05-17T23:52:34.862471Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:52:34.862471Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1902.10016","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":"2026-05-17T23:52:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nAcUSAcqfFyj0+5ciuehnJJTXtDBuYk3P+LezFG0krboYCldOo0HDOe4TL84g2NqmEVJ34t8cktX6akecYETCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T01:13:55.629577Z"},"content_sha256":"109ea900e1355f8ee0cbd3e23120af70bf96454ac13b025fd7c5fca5df5a864b","schema_version":"1.0","event_id":"sha256:109ea900e1355f8ee0cbd3e23120af70bf96454ac13b025fd7c5fca5df5a864b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:B32TIWB4R2PVT2R27BA6DU4K7Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Anomalous Situation Detection in Complex Scenes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Giovanni Sachi, Hina Afridi, Michalis Voutouris","submitted_at":"2019-02-26T15:56:27Z","abstract_excerpt":"In this paper we investigate a robust method to identify anomalies in complex scenes. This task is performed by evaluating the collective behavior by extracting the local binary patterns (LBP) and Laplacian of Gaussian (LoG) features. We fuse both features together which are exploited to train an MLP neural network during the training stage, and the anomaly is identified on the test samples. Considering the challenge of tracking individuals in dense crowded scenes due to multiple occlusions and clutter, in this paper we extract LBP and LoG features and use them as an approximate representation"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.10016","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":"2026-05-17T23:52:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d4GC9R1SvKPPN6FZKYrY3dWGyy71vr6u7Gd/aI7Q1PWhVVi+n92BdQ/qtRkoa1ysM0iZTCtg0p5vcK/P3IToAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T01:13:55.630336Z"},"content_sha256":"41ed3449ec4e3a7cb40a407906fbede24889662cae4ff78ae132d4a1dcb4fabe","schema_version":"1.0","event_id":"sha256:41ed3449ec4e3a7cb40a407906fbede24889662cae4ff78ae132d4a1dcb4fabe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/B32TIWB4R2PVT2R27BA6DU4K7Z/bundle.json","state_url":"https://pith.science/pith/B32TIWB4R2PVT2R27BA6DU4K7Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/B32TIWB4R2PVT2R27BA6DU4K7Z/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":"2026-05-31T01:13:55Z","links":{"resolver":"https://pith.science/pith/B32TIWB4R2PVT2R27BA6DU4K7Z","bundle":"https://pith.science/pith/B32TIWB4R2PVT2R27BA6DU4K7Z/bundle.json","state":"https://pith.science/pith/B32TIWB4R2PVT2R27BA6DU4K7Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/B32TIWB4R2PVT2R27BA6DU4K7Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:B32TIWB4R2PVT2R27BA6DU4K7Z","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":"620c350f95349f7b5b12dc72842cb41704cacc69edb173dc766f0aabd6369a86","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-26T15:56:27Z","title_canon_sha256":"d53cb22880a171a3784e506dbbcb16ad58965738b616d087dcd1a84b963c3b36"},"schema_version":"1.0","source":{"id":"1902.10016","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.10016","created_at":"2026-05-17T23:52:34Z"},{"alias_kind":"arxiv_version","alias_value":"1902.10016v1","created_at":"2026-05-17T23:52:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.10016","created_at":"2026-05-17T23:52:34Z"},{"alias_kind":"pith_short_12","alias_value":"B32TIWB4R2PV","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"B32TIWB4R2PVT2R2","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"B32TIWB4","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:41ed3449ec4e3a7cb40a407906fbede24889662cae4ff78ae132d4a1dcb4fabe","target":"graph","created_at":"2026-05-17T23:52:34Z","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":"In this paper we investigate a robust method to identify anomalies in complex scenes. This task is performed by evaluating the collective behavior by extracting the local binary patterns (LBP) and Laplacian of Gaussian (LoG) features. We fuse both features together which are exploited to train an MLP neural network during the training stage, and the anomaly is identified on the test samples. Considering the challenge of tracking individuals in dense crowded scenes due to multiple occlusions and clutter, in this paper we extract LBP and LoG features and use them as an approximate representation","authors_text":"Giovanni Sachi, Hina Afridi, Michalis Voutouris","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-26T15:56:27Z","title":"Anomalous Situation Detection in Complex Scenes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.10016","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":"sha256:109ea900e1355f8ee0cbd3e23120af70bf96454ac13b025fd7c5fca5df5a864b","target":"record","created_at":"2026-05-17T23:52:34Z","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":"620c350f95349f7b5b12dc72842cb41704cacc69edb173dc766f0aabd6369a86","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-26T15:56:27Z","title_canon_sha256":"d53cb22880a171a3784e506dbbcb16ad58965738b616d087dcd1a84b963c3b36"},"schema_version":"1.0","source":{"id":"1902.10016","kind":"arxiv","version":1}},"canonical_sha256":"0ef534583c8e9f59ea3af841e1d38afe565a4db030e02f5982bd5cb876244fdb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0ef534583c8e9f59ea3af841e1d38afe565a4db030e02f5982bd5cb876244fdb","first_computed_at":"2026-05-17T23:52:34.862471Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:52:34.862471Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"R+p/WuDdVgJZzNCxcR9G1CG928wCw36jXPpUs1P2uEH7+EpRSPYIFMadW8zbLDOkpGhIdgZxWjVkIwvPT3huCA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:52:34.862891Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.10016","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:109ea900e1355f8ee0cbd3e23120af70bf96454ac13b025fd7c5fca5df5a864b","sha256:41ed3449ec4e3a7cb40a407906fbede24889662cae4ff78ae132d4a1dcb4fabe"],"state_sha256":"e78c0cae0787a493b196f2e0db46b7585e97e12d59558e6d0eb947efc0be0f9c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q5CLp3x6Bpd/JWrIDY2/AfslZA/iQMNZXda3uvRbFTQVl+z+GiZxbSB7zgv6rcpJRsfsNziCPyZ0Y75cX0nEAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T01:13:55.634995Z","bundle_sha256":"8531ec09b56468abbada5a77f5f0c0f5adb967571e4f063cdd24c8c873be76c9"}}