{"id":"W2903602498","doi":"10.1016/j.optlaseng.2018.11.014","title":"Real-time 3D surface-shape measurement using background-modulated modified Fourier transform profilometry with geometry-constraint","year":2018,"lang":"en","type":"article","venue":"Optics and Lasers in Engineering","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; University of Waterloo","keywords":"Profilometer; Structured-light 3D scanner; Projector; Computer science; Fourier transform; Point (geometry); Calibration; Optics; Artificial intelligence; Computer vision; Algorithm; Geometry; Mathematics; Surface finish; Physics; Materials science; Mathematical analysis","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006271632,0.0002366675,0.000250359,0.000230322,0.00006639769,0.000170482,0.0002839579,0.000102237,0.0000194679],"category_scores_gemma":[0.00002648988,0.0002051611,0.0000313356,0.000587541,0.00008743418,0.0003705883,0.00006316278,0.0001893866,0.000003149793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001279159,"about_ca_system_score_gemma":0.0000530711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003451521,"about_ca_topic_score_gemma":0.000007612216,"domain_scores_codex":[0.998487,0.0000149654,0.0002812826,0.0003565932,0.0004328115,0.0004273728],"domain_scores_gemma":[0.9993224,0.00002665994,0.00004446401,0.0002866306,0.000187732,0.000132093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002124984,0.0005171699,0.001754102,0.0005687122,0.0004281552,0.000102822,0.001426414,0.03999946,0.8819745,0.02981106,0.00004232415,0.0431628],"study_design_scores_gemma":[0.0003786873,0.0003648871,0.0004317041,0.000284281,0.00001349248,0.000009674179,0.00002462674,0.9727845,0.02530528,0.00007679934,0.00001875244,0.0003073552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.682968,0.00002277619,0.3137838,0.00006129057,0.00008894542,0.0002460372,0.000001906955,0.0001720886,0.002655217],"genre_scores_gemma":[0.7276745,0.00002371088,0.2722336,0.00001014714,0.00002679025,0.000004824732,8.953982e-7,0.00001605079,0.000009504745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.932785,"threshold_uncertainty_score":0.8366228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.034757414972583,"score_gpt":0.2422246422808086,"score_spread":0.2074672273082256,"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."}}