{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:FDHKFVBWMHNKGRD7ID3OPGBJGI","short_pith_number":"pith:FDHKFVBW","schema_version":"1.0","canonical_sha256":"28cea2d43661daa3447f40f6e79829323f963964737b4ae9357a46c4eed32a9f","source":{"kind":"arxiv","id":"1401.5311","version":2},"attestation_state":"computed","paper":{"title":"Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Changxing Ding, Dacheng Tao, Jonghyun Choi, Larry S. Davis","submitted_at":"2014-01-21T13:24:16Z","abstract_excerpt":"To perform unconstrained face recognition robust to variations in illumination, pose and expression, this paper presents a new scheme to extract \"Multi-Directional Multi-Level Dual-Cross Patterns\" (MDML-DCPs) from face images. Specifically, the MDMLDCPs scheme exploits the first derivative of Gaussian operator to reduce the impact of differences in illumination and then computes the DCP feature at both the holistic and component levels. DCP is a novel face image descriptor inspired by the unique textural structure of human faces. It is computationally efficient and only doubles the cost of com"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1401.5311","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-01-21T13:24:16Z","cross_cats_sorted":[],"title_canon_sha256":"cdea6f9289e957f23b53f84541583866ed1cf34de41565fda69f05a16114e2b0","abstract_canon_sha256":"eb7d5a82f34a34b955d33017c354471b35d063c66126395c9806f72670f946da"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:35:43.713178Z","signature_b64":"q/g1VFuok8hUDsONe99vgKZvA59lxeOFrREoIZAZNFRNXFwA+qijKHiAuABQaOkeEGc4o0Bkqv6U2XbRM3CEDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"28cea2d43661daa3447f40f6e79829323f963964737b4ae9357a46c4eed32a9f","last_reissued_at":"2026-05-18T01:35:43.712781Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:35:43.712781Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Changxing Ding, Dacheng Tao, Jonghyun Choi, Larry S. Davis","submitted_at":"2014-01-21T13:24:16Z","abstract_excerpt":"To perform unconstrained face recognition robust to variations in illumination, pose and expression, this paper presents a new scheme to extract \"Multi-Directional Multi-Level Dual-Cross Patterns\" (MDML-DCPs) from face images. Specifically, the MDMLDCPs scheme exploits the first derivative of Gaussian operator to reduce the impact of differences in illumination and then computes the DCP feature at both the holistic and component levels. DCP is a novel face image descriptor inspired by the unique textural structure of human faces. It is computationally efficient and only doubles the cost of com"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1401.5311","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1401.5311","created_at":"2026-05-18T01:35:43.712838+00:00"},{"alias_kind":"arxiv_version","alias_value":"1401.5311v2","created_at":"2026-05-18T01:35:43.712838+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1401.5311","created_at":"2026-05-18T01:35:43.712838+00:00"},{"alias_kind":"pith_short_12","alias_value":"FDHKFVBWMHNK","created_at":"2026-05-18T12:28:28.263976+00:00"},{"alias_kind":"pith_short_16","alias_value":"FDHKFVBWMHNKGRD7","created_at":"2026-05-18T12:28:28.263976+00:00"},{"alias_kind":"pith_short_8","alias_value":"FDHKFVBW","created_at":"2026-05-18T12:28:28.263976+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/FDHKFVBWMHNKGRD7ID3OPGBJGI","json":"https://pith.science/pith/FDHKFVBWMHNKGRD7ID3OPGBJGI.json","graph_json":"https://pith.science/api/pith-number/FDHKFVBWMHNKGRD7ID3OPGBJGI/graph.json","events_json":"https://pith.science/api/pith-number/FDHKFVBWMHNKGRD7ID3OPGBJGI/events.json","paper":"https://pith.science/paper/FDHKFVBW"},"agent_actions":{"view_html":"https://pith.science/pith/FDHKFVBWMHNKGRD7ID3OPGBJGI","download_json":"https://pith.science/pith/FDHKFVBWMHNKGRD7ID3OPGBJGI.json","view_paper":"https://pith.science/paper/FDHKFVBW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1401.5311&json=true","fetch_graph":"https://pith.science/api/pith-number/FDHKFVBWMHNKGRD7ID3OPGBJGI/graph.json","fetch_events":"https://pith.science/api/pith-number/FDHKFVBWMHNKGRD7ID3OPGBJGI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FDHKFVBWMHNKGRD7ID3OPGBJGI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FDHKFVBWMHNKGRD7ID3OPGBJGI/action/storage_attestation","attest_author":"https://pith.science/pith/FDHKFVBWMHNKGRD7ID3OPGBJGI/action/author_attestation","sign_citation":"https://pith.science/pith/FDHKFVBWMHNKGRD7ID3OPGBJGI/action/citation_signature","submit_replication":"https://pith.science/pith/FDHKFVBWMHNKGRD7ID3OPGBJGI/action/replication_record"}},"created_at":"2026-05-18T01:35:43.712838+00:00","updated_at":"2026-05-18T01:35:43.712838+00:00"}