{"id":"W2541126860","doi":"10.1117/12.411811","title":"&lt;title&gt;Estimation of large-amplitude motion and disparity fields: application to intermediate view reconstruction&lt;/title&gt;","year":2000,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Delaunay triangulation; Classification of discontinuities; Optical flow; Computer vision; Artificial intelligence; Computer science; Interpolation (computer graphics); Motion estimation; Feature (linguistics); Algorithm; Mathematics; Motion (physics); Image (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002050332,0.00009888824,0.0001427312,0.00005043902,0.00003512232,0.00004450851,0.0003295659,0.0000585392,0.00004148253],"category_scores_gemma":[0.0001161326,0.0000869386,0.0001039047,0.0001661263,0.00005169499,0.0003518828,0.00007586594,0.00009396121,0.00001001283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003860301,"about_ca_system_score_gemma":0.000008783356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001080318,"about_ca_topic_score_gemma":6.116402e-8,"domain_scores_codex":[0.9992002,1.882877e-8,0.0002702761,0.0001916356,0.0002128834,0.0001249919],"domain_scores_gemma":[0.999445,0.00003202871,0.0001153746,0.00004622054,0.000308877,0.00005253136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001375363,0.00005925462,0.0000740972,0.0002408406,0.00005451273,2.313147e-8,0.000156195,0.0001792443,0.04188116,0.7300546,0.00249184,0.2247945],"study_design_scores_gemma":[0.0006134049,0.0001524534,0.002566112,0.0004173237,0.00004936567,0.00002166679,0.0000924359,0.9272706,0.02115499,0.01316697,0.0341432,0.000351461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8943418,0.0001675202,0.09270407,0.001833768,0.0002652266,0.0004106288,0.0000178846,0.00009420597,0.01016494],"genre_scores_gemma":[0.5824278,0.0002396303,0.4165332,0.0001781883,0.0001688773,0.00006057338,0.000005775528,0.00002126655,0.0003646849],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9270914,"threshold_uncertainty_score":0.3545253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00759840163892181,"score_gpt":0.2435296234938833,"score_spread":0.2359312218549615,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}