{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:LFJVSOO27NGXFI4IHDXK5P2TYS","short_pith_number":"pith:LFJVSOO2","schema_version":"1.0","canonical_sha256":"59535939dafb4d72a38838eeaebf53c4b8143e32a6214a5c8212a4be9f90a373","source":{"kind":"arxiv","id":"1907.11458","version":1},"attestation_state":"computed","paper":{"title":"Multiple Human Association between Top and Horizontal Views by Matching Subjects' Spatial Distributions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Chenxing Gong, Jiewen Zhao, Liang Wan, Ruize Han, Song Wang, Wei Feng, Xiaoyu Zhang, Yujun Zhang","submitted_at":"2019-07-26T09:47:17Z","abstract_excerpt":"Video surveillance can be significantly enhanced by using both top-view data, e.g., those from drone-mounted cameras in the air, and horizontal-view data, e.g., those from wearable cameras on the ground. Collaborative analysis of different-view data can facilitate various kinds of applications, such as human tracking, person identification, and human activity recognition. However, for such collaborative analysis, the first step is to associate people, referred to as subjects in this paper, across these two views. This is a very challenging problem due to large human-appearance difference betwe"},"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":"1907.11458","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-26T09:47:17Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"25b17dafb56bbe9ca3f98048c75110824deb6e689f791ddd55a23712a78e010a","abstract_canon_sha256":"333552d9da067e3f9c6e76efada522df8a5b3138f10bad5d7f41c3236ba7e21a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:29.025636Z","signature_b64":"to+OG/51Qt+zR5JUgvwinH9N0exha8nnSTFh9eVx4Dmcyj3oEysRxbmQWqLjeZu6leF1d7kpHxANjNT0hUcnAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"59535939dafb4d72a38838eeaebf53c4b8143e32a6214a5c8212a4be9f90a373","last_reissued_at":"2026-05-17T23:39:29.024775Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:29.024775Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multiple Human Association between Top and Horizontal Views by Matching Subjects' Spatial Distributions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Chenxing Gong, Jiewen Zhao, Liang Wan, Ruize Han, Song Wang, Wei Feng, Xiaoyu Zhang, Yujun Zhang","submitted_at":"2019-07-26T09:47:17Z","abstract_excerpt":"Video surveillance can be significantly enhanced by using both top-view data, e.g., those from drone-mounted cameras in the air, and horizontal-view data, e.g., those from wearable cameras on the ground. Collaborative analysis of different-view data can facilitate various kinds of applications, such as human tracking, person identification, and human activity recognition. However, for such collaborative analysis, the first step is to associate people, referred to as subjects in this paper, across these two views. This is a very challenging problem due to large human-appearance difference betwe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.11458","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1907.11458","created_at":"2026-05-17T23:39:29.024916+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.11458v1","created_at":"2026-05-17T23:39:29.024916+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.11458","created_at":"2026-05-17T23:39:29.024916+00:00"},{"alias_kind":"pith_short_12","alias_value":"LFJVSOO27NGX","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_16","alias_value":"LFJVSOO27NGXFI4I","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_8","alias_value":"LFJVSOO2","created_at":"2026-05-18T12:33:21.387695+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/LFJVSOO27NGXFI4IHDXK5P2TYS","json":"https://pith.science/pith/LFJVSOO27NGXFI4IHDXK5P2TYS.json","graph_json":"https://pith.science/api/pith-number/LFJVSOO27NGXFI4IHDXK5P2TYS/graph.json","events_json":"https://pith.science/api/pith-number/LFJVSOO27NGXFI4IHDXK5P2TYS/events.json","paper":"https://pith.science/paper/LFJVSOO2"},"agent_actions":{"view_html":"https://pith.science/pith/LFJVSOO27NGXFI4IHDXK5P2TYS","download_json":"https://pith.science/pith/LFJVSOO27NGXFI4IHDXK5P2TYS.json","view_paper":"https://pith.science/paper/LFJVSOO2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.11458&json=true","fetch_graph":"https://pith.science/api/pith-number/LFJVSOO27NGXFI4IHDXK5P2TYS/graph.json","fetch_events":"https://pith.science/api/pith-number/LFJVSOO27NGXFI4IHDXK5P2TYS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LFJVSOO27NGXFI4IHDXK5P2TYS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LFJVSOO27NGXFI4IHDXK5P2TYS/action/storage_attestation","attest_author":"https://pith.science/pith/LFJVSOO27NGXFI4IHDXK5P2TYS/action/author_attestation","sign_citation":"https://pith.science/pith/LFJVSOO27NGXFI4IHDXK5P2TYS/action/citation_signature","submit_replication":"https://pith.science/pith/LFJVSOO27NGXFI4IHDXK5P2TYS/action/replication_record"}},"created_at":"2026-05-17T23:39:29.024916+00:00","updated_at":"2026-05-17T23:39:29.024916+00:00"}