{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:M4LIBAPBPAQ3RKEAGYIENI37JY","short_pith_number":"pith:M4LIBAPB","schema_version":"1.0","canonical_sha256":"67168081e17821b8a880361046a37f4e2b7358e498100bdeb46ca4a642971619","source":{"kind":"arxiv","id":"2607.25146","version":1},"attestation_state":"computed","paper":{"title":"FIDAC: An Easy-to-use Pipeline to Extract and Interpret Interpersonal Distance From Video","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.HC"],"primary_cat":"cs.CV","authors_text":"Eugy Han, Jeremy N. Bailenson, Keshav Rastogi","submitted_at":"2026-07-27T23:44:34Z","abstract_excerpt":"The distance between persons reveals significant information about their perception of each other. However, such information is not easily extractable and interpretable from video input. We developed an open-sourced library, Facial Interpersonal Distance Analysis and Coding (FIDAC) that transforms facial detection results into actionable data about location and interpersonal distance. This tool merges data from multiple open-source facial detection models, strategically compensating for gaps in any individual model. In addition, we include methods for more accurate tracking, such as a pipeline"},"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":"2607.25146","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-27T23:44:34Z","cross_cats_sorted":["cs.HC"],"title_canon_sha256":"c6a0476e7b6366ccf660f2bedd7720b9cada3d210a0542e3f488e278898ace22","abstract_canon_sha256":"510faecf895c52739109756675f2d52de0a62a428024dc42658043a637f6f7be"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-29T00:25:05.272634Z","signature_b64":"lq26cFdbTaoB2ij8Fw8w6SDEX8zLsv1LkjcGBcul4W23w5GpCtKMXMYmu2Rml0WuSrGujbegPrT8dPx/n4QUAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"67168081e17821b8a880361046a37f4e2b7358e498100bdeb46ca4a642971619","last_reissued_at":"2026-07-29T00:25:05.271846Z","signature_status":"signed_v1","first_computed_at":"2026-07-29T00:25:05.271846Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FIDAC: An Easy-to-use Pipeline to Extract and Interpret Interpersonal Distance From Video","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.HC"],"primary_cat":"cs.CV","authors_text":"Eugy Han, Jeremy N. Bailenson, Keshav Rastogi","submitted_at":"2026-07-27T23:44:34Z","abstract_excerpt":"The distance between persons reveals significant information about their perception of each other. However, such information is not easily extractable and interpretable from video input. We developed an open-sourced library, Facial Interpersonal Distance Analysis and Coding (FIDAC) that transforms facial detection results into actionable data about location and interpersonal distance. This tool merges data from multiple open-source facial detection models, strategically compensating for gaps in any individual model. In addition, we include methods for more accurate tracking, such as a pipeline"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.25146","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.25146/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2607.25146","created_at":"2026-07-29T00:25:05.272239+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.25146v1","created_at":"2026-07-29T00:25:05.272239+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.25146","created_at":"2026-07-29T00:25:05.272239+00:00"},{"alias_kind":"pith_short_12","alias_value":"M4LIBAPBPAQ3","created_at":"2026-07-29T00:25:05.272239+00:00"},{"alias_kind":"pith_short_16","alias_value":"M4LIBAPBPAQ3RKEA","created_at":"2026-07-29T00:25:05.272239+00:00"},{"alias_kind":"pith_short_8","alias_value":"M4LIBAPB","created_at":"2026-07-29T00:25:05.272239+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/M4LIBAPBPAQ3RKEAGYIENI37JY","json":"https://pith.science/pith/M4LIBAPBPAQ3RKEAGYIENI37JY.json","graph_json":"https://pith.science/api/pith-number/M4LIBAPBPAQ3RKEAGYIENI37JY/graph.json","events_json":"https://pith.science/api/pith-number/M4LIBAPBPAQ3RKEAGYIENI37JY/events.json","paper":"https://pith.science/paper/M4LIBAPB"},"agent_actions":{"view_html":"https://pith.science/pith/M4LIBAPBPAQ3RKEAGYIENI37JY","download_json":"https://pith.science/pith/M4LIBAPBPAQ3RKEAGYIENI37JY.json","view_paper":"https://pith.science/paper/M4LIBAPB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.25146&json=true","fetch_graph":"https://pith.science/api/pith-number/M4LIBAPBPAQ3RKEAGYIENI37JY/graph.json","fetch_events":"https://pith.science/api/pith-number/M4LIBAPBPAQ3RKEAGYIENI37JY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/M4LIBAPBPAQ3RKEAGYIENI37JY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/M4LIBAPBPAQ3RKEAGYIENI37JY/action/storage_attestation","attest_author":"https://pith.science/pith/M4LIBAPBPAQ3RKEAGYIENI37JY/action/author_attestation","sign_citation":"https://pith.science/pith/M4LIBAPBPAQ3RKEAGYIENI37JY/action/citation_signature","submit_replication":"https://pith.science/pith/M4LIBAPBPAQ3RKEAGYIENI37JY/action/replication_record"}},"created_at":"2026-07-29T00:25:05.272239+00:00","updated_at":"2026-07-29T00:25:05.272239+00:00"}