{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:XJ25E7AB6JOUCX3YLZ7OER2YOM","short_pith_number":"pith:XJ25E7AB","schema_version":"1.0","canonical_sha256":"ba75d27c01f25d415f785e7ee24758732dab5cf52cf72e66117a4794db5fe41c","source":{"kind":"arxiv","id":"1806.03483","version":2},"attestation_state":"computed","paper":{"title":"Hierarchical Information Quadtree: Efficient Spatial Temporal Image Search for Multimedia Stream","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.MM","authors_text":"Anfeng Liu, Chengyuan Zhang, Fang Huang, Lei Zhu, Ruipeng Chen, Yunwu Lin","submitted_at":"2018-06-09T14:53:07Z","abstract_excerpt":"Massive amount of multimedia data that contain times- tamps and geographical information are being generated at an unprecedented scale in many emerging applications such as photo sharing web site and social networks applications. Due to their importance, a large body of work has focused on efficiently computing various spatial image queries. In this paper,we study the spatial temporal image query which considers three important constraints during the search including time recency, spatial proximity and visual relevance. A novel index structure, namely Hierarchical Information Quadtree(\\hiq), t"},"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":"1806.03483","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MM","submitted_at":"2018-06-09T14:53:07Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"3eacb364fd9ab079150cb55bf55b0894f270423531bb2acda0c0b1acf7ba9a85","abstract_canon_sha256":"56291230bb78a95ffbf30b54215f92ef261e13ff98c6871e30b02cd1565e52cf"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:08:02.826504Z","signature_b64":"r3VjS9mkCKJmDubdPWWiamj38lxOnGxTaz/UBGj885Cg1svldMc99kInA5nVcGkMszQqKkQCAyT54eWUX8YgCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ba75d27c01f25d415f785e7ee24758732dab5cf52cf72e66117a4794db5fe41c","last_reissued_at":"2026-05-18T00:08:02.825778Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:08:02.825778Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Hierarchical Information Quadtree: Efficient Spatial Temporal Image Search for Multimedia Stream","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.MM","authors_text":"Anfeng Liu, Chengyuan Zhang, Fang Huang, Lei Zhu, Ruipeng Chen, Yunwu Lin","submitted_at":"2018-06-09T14:53:07Z","abstract_excerpt":"Massive amount of multimedia data that contain times- tamps and geographical information are being generated at an unprecedented scale in many emerging applications such as photo sharing web site and social networks applications. Due to their importance, a large body of work has focused on efficiently computing various spatial image queries. In this paper,we study the spatial temporal image query which considers three important constraints during the search including time recency, spatial proximity and visual relevance. A novel index structure, namely Hierarchical Information Quadtree(\\hiq), t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.03483","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":"1806.03483","created_at":"2026-05-18T00:08:02.825909+00:00"},{"alias_kind":"arxiv_version","alias_value":"1806.03483v2","created_at":"2026-05-18T00:08:02.825909+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.03483","created_at":"2026-05-18T00:08:02.825909+00:00"},{"alias_kind":"pith_short_12","alias_value":"XJ25E7AB6JOU","created_at":"2026-05-18T12:33:01.666342+00:00"},{"alias_kind":"pith_short_16","alias_value":"XJ25E7AB6JOUCX3Y","created_at":"2026-05-18T12:33:01.666342+00:00"},{"alias_kind":"pith_short_8","alias_value":"XJ25E7AB","created_at":"2026-05-18T12:33:01.666342+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/XJ25E7AB6JOUCX3YLZ7OER2YOM","json":"https://pith.science/pith/XJ25E7AB6JOUCX3YLZ7OER2YOM.json","graph_json":"https://pith.science/api/pith-number/XJ25E7AB6JOUCX3YLZ7OER2YOM/graph.json","events_json":"https://pith.science/api/pith-number/XJ25E7AB6JOUCX3YLZ7OER2YOM/events.json","paper":"https://pith.science/paper/XJ25E7AB"},"agent_actions":{"view_html":"https://pith.science/pith/XJ25E7AB6JOUCX3YLZ7OER2YOM","download_json":"https://pith.science/pith/XJ25E7AB6JOUCX3YLZ7OER2YOM.json","view_paper":"https://pith.science/paper/XJ25E7AB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1806.03483&json=true","fetch_graph":"https://pith.science/api/pith-number/XJ25E7AB6JOUCX3YLZ7OER2YOM/graph.json","fetch_events":"https://pith.science/api/pith-number/XJ25E7AB6JOUCX3YLZ7OER2YOM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XJ25E7AB6JOUCX3YLZ7OER2YOM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XJ25E7AB6JOUCX3YLZ7OER2YOM/action/storage_attestation","attest_author":"https://pith.science/pith/XJ25E7AB6JOUCX3YLZ7OER2YOM/action/author_attestation","sign_citation":"https://pith.science/pith/XJ25E7AB6JOUCX3YLZ7OER2YOM/action/citation_signature","submit_replication":"https://pith.science/pith/XJ25E7AB6JOUCX3YLZ7OER2YOM/action/replication_record"}},"created_at":"2026-05-18T00:08:02.825909+00:00","updated_at":"2026-05-18T00:08:02.825909+00:00"}