{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:4SOVEC5T4RPT5P7HBNRKURPGC7","short_pith_number":"pith:4SOVEC5T","schema_version":"1.0","canonical_sha256":"e49d520bb3e45f3ebfe70b62aa45e617d5ccf22b0a5a8534bacfcf9a3ddf6b4a","source":{"kind":"arxiv","id":"1707.07075","version":1},"attestation_state":"computed","paper":{"title":"Automatic Curation of Golf Highlights using Multimodal Excitement Features","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"cs.CV","authors_text":"Dhiraj Joshi, John Kent, John R. Smith, Michele Merler, Quoc-Bao Nguyen, Rogerio S. Feris, Stephen Hammer","submitted_at":"2017-07-22T00:06:50Z","abstract_excerpt":"The production of sports highlight packages summarizing a game's most exciting moments is an essential task for broadcast media. Yet, it requires labor-intensive video editing. We propose a novel approach for auto-curating sports highlights, and use it to create a real-world system for the editorial aid of golf highlight reels. Our method fuses information from the players' reactions (action recognition such as high-fives and fist pumps), spectators (crowd cheering), and commentator (tone of the voice and word analysis) to determine the most interesting moments of a game. We accurately identif"},"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":"1707.07075","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-22T00:06:50Z","cross_cats_sorted":["cs.MM"],"title_canon_sha256":"66519e94fc2bd6990a743e91398cf20cb6534291c871a54bf858aa9adfe15411","abstract_canon_sha256":"9cbd1713db697883451e022082b63c965414c5821b48a4eb22edf7c339801c9b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:45.431554Z","signature_b64":"1VphUCifeX5f0Ui1xRD/VUHnKIvLp9alVQzh6veouKz+1xpW+dCvNEhyA+JqORoJT27T2Q8bw/gX+kfL45gZDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e49d520bb3e45f3ebfe70b62aa45e617d5ccf22b0a5a8534bacfcf9a3ddf6b4a","last_reissued_at":"2026-05-18T00:39:45.431034Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:45.431034Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Automatic Curation of Golf Highlights using Multimodal Excitement Features","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"cs.CV","authors_text":"Dhiraj Joshi, John Kent, John R. Smith, Michele Merler, Quoc-Bao Nguyen, Rogerio S. Feris, Stephen Hammer","submitted_at":"2017-07-22T00:06:50Z","abstract_excerpt":"The production of sports highlight packages summarizing a game's most exciting moments is an essential task for broadcast media. Yet, it requires labor-intensive video editing. We propose a novel approach for auto-curating sports highlights, and use it to create a real-world system for the editorial aid of golf highlight reels. Our method fuses information from the players' reactions (action recognition such as high-fives and fist pumps), spectators (crowd cheering), and commentator (tone of the voice and word analysis) to determine the most interesting moments of a game. We accurately identif"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.07075","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":"1707.07075","created_at":"2026-05-18T00:39:45.431129+00:00"},{"alias_kind":"arxiv_version","alias_value":"1707.07075v1","created_at":"2026-05-18T00:39:45.431129+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.07075","created_at":"2026-05-18T00:39:45.431129+00:00"},{"alias_kind":"pith_short_12","alias_value":"4SOVEC5T4RPT","created_at":"2026-05-18T12:31:00.734936+00:00"},{"alias_kind":"pith_short_16","alias_value":"4SOVEC5T4RPT5P7H","created_at":"2026-05-18T12:31:00.734936+00:00"},{"alias_kind":"pith_short_8","alias_value":"4SOVEC5T","created_at":"2026-05-18T12:31:00.734936+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/4SOVEC5T4RPT5P7HBNRKURPGC7","json":"https://pith.science/pith/4SOVEC5T4RPT5P7HBNRKURPGC7.json","graph_json":"https://pith.science/api/pith-number/4SOVEC5T4RPT5P7HBNRKURPGC7/graph.json","events_json":"https://pith.science/api/pith-number/4SOVEC5T4RPT5P7HBNRKURPGC7/events.json","paper":"https://pith.science/paper/4SOVEC5T"},"agent_actions":{"view_html":"https://pith.science/pith/4SOVEC5T4RPT5P7HBNRKURPGC7","download_json":"https://pith.science/pith/4SOVEC5T4RPT5P7HBNRKURPGC7.json","view_paper":"https://pith.science/paper/4SOVEC5T","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1707.07075&json=true","fetch_graph":"https://pith.science/api/pith-number/4SOVEC5T4RPT5P7HBNRKURPGC7/graph.json","fetch_events":"https://pith.science/api/pith-number/4SOVEC5T4RPT5P7HBNRKURPGC7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4SOVEC5T4RPT5P7HBNRKURPGC7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4SOVEC5T4RPT5P7HBNRKURPGC7/action/storage_attestation","attest_author":"https://pith.science/pith/4SOVEC5T4RPT5P7HBNRKURPGC7/action/author_attestation","sign_citation":"https://pith.science/pith/4SOVEC5T4RPT5P7HBNRKURPGC7/action/citation_signature","submit_replication":"https://pith.science/pith/4SOVEC5T4RPT5P7HBNRKURPGC7/action/replication_record"}},"created_at":"2026-05-18T00:39:45.431129+00:00","updated_at":"2026-05-18T00:39:45.431129+00:00"}