{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:H76HDZF72LJRLUVJPUDXD6BHBD","short_pith_number":"pith:H76HDZF7","schema_version":"1.0","canonical_sha256":"3ffc71e4bfd2d315d2a97d0771f82708fdcab04533b8bb5b611d218590d84c9a","source":{"kind":"arxiv","id":"1907.09233","version":1},"attestation_state":"computed","paper":{"title":"Adapting Computer Vision Algorithms for Omnidirectional Video","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hannes Fassold","submitted_at":"2019-07-22T11:12:35Z","abstract_excerpt":"Omnidirectional (360{\\deg}) video has got quite popular because it provides a highly immersive viewing experience. For computer vision algorithms, it poses several challenges, like the special (equirectangular) projection commonly employed and the huge image size. In this work, we give a high-level overview of these challenges and outline strategies how to adapt computer vision algorithm for the specifics of omnidirectional video."},"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":"1907.09233","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T11:12:35Z","cross_cats_sorted":[],"title_canon_sha256":"6a6e34dc7581f0bd50512d4bef9c42d24cba7338d7b582a9bdd041e01b1d05ca","abstract_canon_sha256":"3552357bc6432a1dfbea6aa7947859147ef2e9f7f879d7b2bba96b12df9d4962"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:59.770860Z","signature_b64":"jq+8Ar42SZjZxX8IYqNhsi1oWrprzBM+H9sNOotcrim987lWfS3Abe81rWZa4aVppJmDESIq7DUK8K8gfTIbAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3ffc71e4bfd2d315d2a97d0771f82708fdcab04533b8bb5b611d218590d84c9a","last_reissued_at":"2026-05-17T23:39:59.770397Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:59.770397Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Adapting Computer Vision Algorithms for Omnidirectional Video","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hannes Fassold","submitted_at":"2019-07-22T11:12:35Z","abstract_excerpt":"Omnidirectional (360{\\deg}) video has got quite popular because it provides a highly immersive viewing experience. For computer vision algorithms, it poses several challenges, like the special (equirectangular) projection commonly employed and the huge image size. In this work, we give a high-level overview of these challenges and outline strategies how to adapt computer vision algorithm for the specifics of omnidirectional video."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.09233","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":"1907.09233","created_at":"2026-05-17T23:39:59.770467+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.09233v1","created_at":"2026-05-17T23:39:59.770467+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.09233","created_at":"2026-05-17T23:39:59.770467+00:00"},{"alias_kind":"pith_short_12","alias_value":"H76HDZF72LJR","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_16","alias_value":"H76HDZF72LJRLUVJ","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_8","alias_value":"H76HDZF7","created_at":"2026-05-18T12:33:18.533446+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/H76HDZF72LJRLUVJPUDXD6BHBD","json":"https://pith.science/pith/H76HDZF72LJRLUVJPUDXD6BHBD.json","graph_json":"https://pith.science/api/pith-number/H76HDZF72LJRLUVJPUDXD6BHBD/graph.json","events_json":"https://pith.science/api/pith-number/H76HDZF72LJRLUVJPUDXD6BHBD/events.json","paper":"https://pith.science/paper/H76HDZF7"},"agent_actions":{"view_html":"https://pith.science/pith/H76HDZF72LJRLUVJPUDXD6BHBD","download_json":"https://pith.science/pith/H76HDZF72LJRLUVJPUDXD6BHBD.json","view_paper":"https://pith.science/paper/H76HDZF7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.09233&json=true","fetch_graph":"https://pith.science/api/pith-number/H76HDZF72LJRLUVJPUDXD6BHBD/graph.json","fetch_events":"https://pith.science/api/pith-number/H76HDZF72LJRLUVJPUDXD6BHBD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/H76HDZF72LJRLUVJPUDXD6BHBD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/H76HDZF72LJRLUVJPUDXD6BHBD/action/storage_attestation","attest_author":"https://pith.science/pith/H76HDZF72LJRLUVJPUDXD6BHBD/action/author_attestation","sign_citation":"https://pith.science/pith/H76HDZF72LJRLUVJPUDXD6BHBD/action/citation_signature","submit_replication":"https://pith.science/pith/H76HDZF72LJRLUVJPUDXD6BHBD/action/replication_record"}},"created_at":"2026-05-17T23:39:59.770467+00:00","updated_at":"2026-05-17T23:39:59.770467+00:00"}