{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:4KMAJPDJIW47MM4ELQ3UO5L367","short_pith_number":"pith:4KMAJPDJ","canonical_record":{"source":{"id":"1311.1279","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","primary_cat":"cs.CV","submitted_at":"2013-11-06T03:16:21Z","cross_cats_sorted":[],"title_canon_sha256":"d31e4434fa6ee1e4d727ad036ada64ca9cc59cbc5ef55ba091c136bd2d7a128b","abstract_canon_sha256":"e4c7b9f2509f7dd4b11a43fcd05a6e1f6233e600b2537a7a8b0d8c58efce79fb"},"schema_version":"1.0"},"canonical_sha256":"e29804bc6945b9f633845c3747757bf7d5c3d267836b6d79a82f5a271bb80ae4","source":{"kind":"arxiv","id":"1311.1279","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1311.1279","created_at":"2026-05-18T03:07:53Z"},{"alias_kind":"arxiv_version","alias_value":"1311.1279v1","created_at":"2026-05-18T03:07:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1311.1279","created_at":"2026-05-18T03:07:53Z"},{"alias_kind":"pith_short_12","alias_value":"4KMAJPDJIW47","created_at":"2026-05-18T12:27:34Z"},{"alias_kind":"pith_short_16","alias_value":"4KMAJPDJIW47MM4E","created_at":"2026-05-18T12:27:34Z"},{"alias_kind":"pith_short_8","alias_value":"4KMAJPDJ","created_at":"2026-05-18T12:27:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:4KMAJPDJIW47MM4ELQ3UO5L367","target":"record","payload":{"canonical_record":{"source":{"id":"1311.1279","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","primary_cat":"cs.CV","submitted_at":"2013-11-06T03:16:21Z","cross_cats_sorted":[],"title_canon_sha256":"d31e4434fa6ee1e4d727ad036ada64ca9cc59cbc5ef55ba091c136bd2d7a128b","abstract_canon_sha256":"e4c7b9f2509f7dd4b11a43fcd05a6e1f6233e600b2537a7a8b0d8c58efce79fb"},"schema_version":"1.0"},"canonical_sha256":"e29804bc6945b9f633845c3747757bf7d5c3d267836b6d79a82f5a271bb80ae4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:07:53.842377Z","signature_b64":"TdF37EZmfoaEVKVueLNrEdcA0ehuWxeI39iegxqLHF+4FK38NBgqlW3ylHpfxMZdrmk2Xn/CCvt4EdmfXwUcAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e29804bc6945b9f633845c3747757bf7d5c3d267836b6d79a82f5a271bb80ae4","last_reissued_at":"2026-05-18T03:07:53.841829Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:07:53.841829Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1311.1279","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":"2026-05-18T03:07:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xJyhpF6W90SC5tImNxPVbOcASWWuzcwmvYDy4f7/HJO2I0B5DSvr1e3Y72Eemy8dhG4N3EyonfwXibdg+Q5dCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T00:32:28.078853Z"},"content_sha256":"3f632351fa860722a0308fa747526ed092183d290c54422fc67dac68af04a7c3","schema_version":"1.0","event_id":"sha256:3f632351fa860722a0308fa747526ed092183d290c54422fc67dac68af04a7c3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:4KMAJPDJIW47MM4ELQ3UO5L367","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Face Recognition via Globality-Locality Preserving Projections","license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dan Yang, Fei Yang, Jiwen Lu, Sheng Huang, Xiaohong Zhang, Yongxin Ge","submitted_at":"2013-11-06T03:16:21Z","abstract_excerpt":"We present an improved Locality Preserving Projections (LPP) method, named Gloablity-Locality Preserving Projections (GLPP), to preserve both the global and local geometric structures of data. In our approach, an additional constraint of the geometry of classes is imposed to the objective function of conventional LPP for respecting some more global manifold structures. Moreover, we formulate a two-dimensional extension of GLPP (2D-GLPP) as an example to show how to extend GLPP with some other statistical techniques. We apply our works to face recognition on four popular face databases, namely "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1311.1279","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":"2026-05-18T03:07:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lh/D8axUxaKzaPJhAm/iD9z5AGjoyXfG/NTn5GkbUFMdOZE1O+77tvCEgyJX+a8mPV2c0S+BhJgxPBCt2xJCBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T00:32:28.079204Z"},"content_sha256":"c771dbd3289e4eadb1b012d86bf6ffb9263e10f36ac03816045e30b894b77800","schema_version":"1.0","event_id":"sha256:c771dbd3289e4eadb1b012d86bf6ffb9263e10f36ac03816045e30b894b77800"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4KMAJPDJIW47MM4ELQ3UO5L367/bundle.json","state_url":"https://pith.science/pith/4KMAJPDJIW47MM4ELQ3UO5L367/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4KMAJPDJIW47MM4ELQ3UO5L367/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":"2026-06-04T00:32:28Z","links":{"resolver":"https://pith.science/pith/4KMAJPDJIW47MM4ELQ3UO5L367","bundle":"https://pith.science/pith/4KMAJPDJIW47MM4ELQ3UO5L367/bundle.json","state":"https://pith.science/pith/4KMAJPDJIW47MM4ELQ3UO5L367/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4KMAJPDJIW47MM4ELQ3UO5L367/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:4KMAJPDJIW47MM4ELQ3UO5L367","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":"e4c7b9f2509f7dd4b11a43fcd05a6e1f6233e600b2537a7a8b0d8c58efce79fb","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","primary_cat":"cs.CV","submitted_at":"2013-11-06T03:16:21Z","title_canon_sha256":"d31e4434fa6ee1e4d727ad036ada64ca9cc59cbc5ef55ba091c136bd2d7a128b"},"schema_version":"1.0","source":{"id":"1311.1279","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1311.1279","created_at":"2026-05-18T03:07:53Z"},{"alias_kind":"arxiv_version","alias_value":"1311.1279v1","created_at":"2026-05-18T03:07:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1311.1279","created_at":"2026-05-18T03:07:53Z"},{"alias_kind":"pith_short_12","alias_value":"4KMAJPDJIW47","created_at":"2026-05-18T12:27:34Z"},{"alias_kind":"pith_short_16","alias_value":"4KMAJPDJIW47MM4E","created_at":"2026-05-18T12:27:34Z"},{"alias_kind":"pith_short_8","alias_value":"4KMAJPDJ","created_at":"2026-05-18T12:27:34Z"}],"graph_snapshots":[{"event_id":"sha256:c771dbd3289e4eadb1b012d86bf6ffb9263e10f36ac03816045e30b894b77800","target":"graph","created_at":"2026-05-18T03:07:53Z","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":"We present an improved Locality Preserving Projections (LPP) method, named Gloablity-Locality Preserving Projections (GLPP), to preserve both the global and local geometric structures of data. In our approach, an additional constraint of the geometry of classes is imposed to the objective function of conventional LPP for respecting some more global manifold structures. Moreover, we formulate a two-dimensional extension of GLPP (2D-GLPP) as an example to show how to extend GLPP with some other statistical techniques. We apply our works to face recognition on four popular face databases, namely ","authors_text":"Dan Yang, Fei Yang, Jiwen Lu, Sheng Huang, Xiaohong Zhang, Yongxin Ge","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","primary_cat":"cs.CV","submitted_at":"2013-11-06T03:16:21Z","title":"Face Recognition via Globality-Locality Preserving Projections"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1311.1279","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":"sha256:3f632351fa860722a0308fa747526ed092183d290c54422fc67dac68af04a7c3","target":"record","created_at":"2026-05-18T03:07:53Z","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":"e4c7b9f2509f7dd4b11a43fcd05a6e1f6233e600b2537a7a8b0d8c58efce79fb","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","primary_cat":"cs.CV","submitted_at":"2013-11-06T03:16:21Z","title_canon_sha256":"d31e4434fa6ee1e4d727ad036ada64ca9cc59cbc5ef55ba091c136bd2d7a128b"},"schema_version":"1.0","source":{"id":"1311.1279","kind":"arxiv","version":1}},"canonical_sha256":"e29804bc6945b9f633845c3747757bf7d5c3d267836b6d79a82f5a271bb80ae4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e29804bc6945b9f633845c3747757bf7d5c3d267836b6d79a82f5a271bb80ae4","first_computed_at":"2026-05-18T03:07:53.841829Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:07:53.841829Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TdF37EZmfoaEVKVueLNrEdcA0ehuWxeI39iegxqLHF+4FK38NBgqlW3ylHpfxMZdrmk2Xn/CCvt4EdmfXwUcAg==","signature_status":"signed_v1","signed_at":"2026-05-18T03:07:53.842377Z","signed_message":"canonical_sha256_bytes"},"source_id":"1311.1279","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3f632351fa860722a0308fa747526ed092183d290c54422fc67dac68af04a7c3","sha256:c771dbd3289e4eadb1b012d86bf6ffb9263e10f36ac03816045e30b894b77800"],"state_sha256":"e5b7dd3bf03ec00150a2ddb755aeb30e7b0708b10d7e9bd1c71dde3f62d81e08"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eIiC2QogzpyTELoq3SeuxBlhhTKyXB9nfOnwUFwoBTEODra4KmZgvV3Y6rcuThD/q4gBhNr9rNI1a3tJRw0fBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T00:32:28.081240Z","bundle_sha256":"575c10656a1ef6eb61d7183f96549a2f4f3c1c9747511a640dd9e4f05f7c64aa"}}