{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:2Z567QVKMSATIG26ZCVVWS4L2J","short_pith_number":"pith:2Z567QVK","schema_version":"1.0","canonical_sha256":"d67befc2aa6481341b5ec8ab5b4b8bd279ea023317d6dea5fb8388edb97d6cc0","source":{"kind":"arxiv","id":"1707.01698","version":1},"attestation_state":"computed","paper":{"title":"Automated Lane Detection in Crowds using Proximity Graphs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Claudio Martella, Maarten van Steen, Nelly Litvak, Stijn Heldens","submitted_at":"2017-07-06T09:23:07Z","abstract_excerpt":"Studying the behavior of crowds is vital for understanding and predicting human interactions in public areas. Research has shown that, under certain conditions, large groups of people can form collective behavior patterns: local interactions between individuals results in global movements patterns. To detect these patterns in a crowd, we assume each person is carrying an on-body device that acts a local proximity sensor, e.g., smartphone or bluetooth badge, and represent the texture of the crowd as a proximity graph. Our goal is extract information about crowds from these proximity graphs. In "},"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":"1707.01698","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-06T09:23:07Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"9945efba033a82be543a22771238a91a186b23d38ee3cec6300809374ca695e1","abstract_canon_sha256":"0b57d1cdf6dc2de3d9d250b8c28515d35651d8a12d0b558c947750d68b2103db"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:40:47.775910Z","signature_b64":"aHRvSdYBgxkcZ/XVAdTfEc9uASj7rO5nJxOaFBmskfYaN++Bu9fdVYYKCZcA6g4OHcI3N1fvW2w8KCzhURX+Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d67befc2aa6481341b5ec8ab5b4b8bd279ea023317d6dea5fb8388edb97d6cc0","last_reissued_at":"2026-05-18T00:40:47.775217Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:40:47.775217Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Automated Lane Detection in Crowds using Proximity Graphs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Claudio Martella, Maarten van Steen, Nelly Litvak, Stijn Heldens","submitted_at":"2017-07-06T09:23:07Z","abstract_excerpt":"Studying the behavior of crowds is vital for understanding and predicting human interactions in public areas. Research has shown that, under certain conditions, large groups of people can form collective behavior patterns: local interactions between individuals results in global movements patterns. To detect these patterns in a crowd, we assume each person is carrying an on-body device that acts a local proximity sensor, e.g., smartphone or bluetooth badge, and represent the texture of the crowd as a proximity graph. Our goal is extract information about crowds from these proximity graphs. In "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.01698","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":"1707.01698","created_at":"2026-05-18T00:40:47.775311+00:00"},{"alias_kind":"arxiv_version","alias_value":"1707.01698v1","created_at":"2026-05-18T00:40:47.775311+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.01698","created_at":"2026-05-18T00:40:47.775311+00:00"},{"alias_kind":"pith_short_12","alias_value":"2Z567QVKMSAT","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_16","alias_value":"2Z567QVKMSATIG26","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_8","alias_value":"2Z567QVK","created_at":"2026-05-18T12:30:55.937587+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/2Z567QVKMSATIG26ZCVVWS4L2J","json":"https://pith.science/pith/2Z567QVKMSATIG26ZCVVWS4L2J.json","graph_json":"https://pith.science/api/pith-number/2Z567QVKMSATIG26ZCVVWS4L2J/graph.json","events_json":"https://pith.science/api/pith-number/2Z567QVKMSATIG26ZCVVWS4L2J/events.json","paper":"https://pith.science/paper/2Z567QVK"},"agent_actions":{"view_html":"https://pith.science/pith/2Z567QVKMSATIG26ZCVVWS4L2J","download_json":"https://pith.science/pith/2Z567QVKMSATIG26ZCVVWS4L2J.json","view_paper":"https://pith.science/paper/2Z567QVK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1707.01698&json=true","fetch_graph":"https://pith.science/api/pith-number/2Z567QVKMSATIG26ZCVVWS4L2J/graph.json","fetch_events":"https://pith.science/api/pith-number/2Z567QVKMSATIG26ZCVVWS4L2J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2Z567QVKMSATIG26ZCVVWS4L2J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2Z567QVKMSATIG26ZCVVWS4L2J/action/storage_attestation","attest_author":"https://pith.science/pith/2Z567QVKMSATIG26ZCVVWS4L2J/action/author_attestation","sign_citation":"https://pith.science/pith/2Z567QVKMSATIG26ZCVVWS4L2J/action/citation_signature","submit_replication":"https://pith.science/pith/2Z567QVKMSATIG26ZCVVWS4L2J/action/replication_record"}},"created_at":"2026-05-18T00:40:47.775311+00:00","updated_at":"2026-05-18T00:40:47.775311+00:00"}