{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:YCVOZ2IQI4LSD2UJDXVW63M2OD","short_pith_number":"pith:YCVOZ2IQ","schema_version":"1.0","canonical_sha256":"c0aaece910471721ea891deb6f6d9a70dab4755d7067905b3110dd7a4e862a56","source":{"kind":"arxiv","id":"1605.00572","version":1},"attestation_state":"computed","paper":{"title":"Comparison of Optimization Methods in Optical Flow Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Noranart Vesdapunt, Utkarsh Sinha","submitted_at":"2016-05-02T17:21:22Z","abstract_excerpt":"Optical flow estimation is a widely known problem in computer vision introduced by Gibson, J.J(1950) to describe the visual perception of human by stimulus objects. Estimation of optical flow model can be achieved by solving for the motion vectors from region of interest in the the different timeline. In this paper, we assumed slightly uniform change of velocity between two nearby frames, and solve the optical flow problem by traditional method, Lucas-Kanade(1981). This method performs minimization of errors between template and target frame warped back onto the template. Solving minimization "},"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":"1605.00572","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-05-02T17:21:22Z","cross_cats_sorted":[],"title_canon_sha256":"230489c49f40f4aee6aa6197a7ebbddc7105aee6e42d94af4505cdd1919fe253","abstract_canon_sha256":"d9155e854cbc3f0062347d84298baa9504f38bb65dd13d22b51c6f54a5c332b3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:15:53.858670Z","signature_b64":"m8+E8R4V2I+1br0O29+cy1QNLLm8d7t/8oSPiKj/Gblw39+cL4Cbid8Qaed5XTRPABrnvyF55Liu3gBlQIm3Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c0aaece910471721ea891deb6f6d9a70dab4755d7067905b3110dd7a4e862a56","last_reissued_at":"2026-05-18T01:15:53.858003Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:15:53.858003Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Comparison of Optimization Methods in Optical Flow Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Noranart Vesdapunt, Utkarsh Sinha","submitted_at":"2016-05-02T17:21:22Z","abstract_excerpt":"Optical flow estimation is a widely known problem in computer vision introduced by Gibson, J.J(1950) to describe the visual perception of human by stimulus objects. Estimation of optical flow model can be achieved by solving for the motion vectors from region of interest in the the different timeline. In this paper, we assumed slightly uniform change of velocity between two nearby frames, and solve the optical flow problem by traditional method, Lucas-Kanade(1981). This method performs minimization of errors between template and target frame warped back onto the template. Solving minimization "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.00572","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":"1605.00572","created_at":"2026-05-18T01:15:53.858087+00:00"},{"alias_kind":"arxiv_version","alias_value":"1605.00572v1","created_at":"2026-05-18T01:15:53.858087+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.00572","created_at":"2026-05-18T01:15:53.858087+00:00"},{"alias_kind":"pith_short_12","alias_value":"YCVOZ2IQI4LS","created_at":"2026-05-18T12:30:53.716459+00:00"},{"alias_kind":"pith_short_16","alias_value":"YCVOZ2IQI4LSD2UJ","created_at":"2026-05-18T12:30:53.716459+00:00"},{"alias_kind":"pith_short_8","alias_value":"YCVOZ2IQ","created_at":"2026-05-18T12:30:53.716459+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/YCVOZ2IQI4LSD2UJDXVW63M2OD","json":"https://pith.science/pith/YCVOZ2IQI4LSD2UJDXVW63M2OD.json","graph_json":"https://pith.science/api/pith-number/YCVOZ2IQI4LSD2UJDXVW63M2OD/graph.json","events_json":"https://pith.science/api/pith-number/YCVOZ2IQI4LSD2UJDXVW63M2OD/events.json","paper":"https://pith.science/paper/YCVOZ2IQ"},"agent_actions":{"view_html":"https://pith.science/pith/YCVOZ2IQI4LSD2UJDXVW63M2OD","download_json":"https://pith.science/pith/YCVOZ2IQI4LSD2UJDXVW63M2OD.json","view_paper":"https://pith.science/paper/YCVOZ2IQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1605.00572&json=true","fetch_graph":"https://pith.science/api/pith-number/YCVOZ2IQI4LSD2UJDXVW63M2OD/graph.json","fetch_events":"https://pith.science/api/pith-number/YCVOZ2IQI4LSD2UJDXVW63M2OD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YCVOZ2IQI4LSD2UJDXVW63M2OD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YCVOZ2IQI4LSD2UJDXVW63M2OD/action/storage_attestation","attest_author":"https://pith.science/pith/YCVOZ2IQI4LSD2UJDXVW63M2OD/action/author_attestation","sign_citation":"https://pith.science/pith/YCVOZ2IQI4LSD2UJDXVW63M2OD/action/citation_signature","submit_replication":"https://pith.science/pith/YCVOZ2IQI4LSD2UJDXVW63M2OD/action/replication_record"}},"created_at":"2026-05-18T01:15:53.858087+00:00","updated_at":"2026-05-18T01:15:53.858087+00:00"}