{"id":"W2113731879","doi":"10.1109/im.2003.1240253","title":"Multi-projectors for arbitrary surfaces without explicit calibration nor reconstruction","year":2004,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Projector; Computer vision; Artificial intelligence; Projection (relational algebra); Computer science; Computer graphics (images); Observer (physics); Pixel; Position (finance); Camera resectioning; Orientation (vector space); Pinhole camera model; Camera auto-calibration; Shadow (psychology); Distortion (music); Structured light; Mathematics; Geometry; Algorithm; Physics","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":[0.00006989029,0.0001057832,0.0001008498,0.00007712426,0.000119532,0.00009324219,0.0002162927,0.00004572893,0.00001691143],"category_scores_gemma":[0.00002283746,0.00008968307,0.00007011415,0.0001325911,0.00001730988,0.001499921,0.0000337583,0.00006265469,0.0000250973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005141174,"about_ca_system_score_gemma":0.00007202096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001870149,"about_ca_topic_score_gemma":0.00006817377,"domain_scores_codex":[0.9992771,0.00001753139,0.0001499216,0.0002975801,0.00008443017,0.0001734749],"domain_scores_gemma":[0.9995807,0.00003367445,0.00006731561,0.0001818011,0.00009572597,0.0000407782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001139346,0.0003253359,0.00967914,0.00005345676,0.0001116036,0.000004557415,0.003836749,0.001018071,0.8537549,0.1227882,0.0007477316,0.00756638],"study_design_scores_gemma":[0.001619778,0.0002685216,0.01168744,0.00004375233,0.00001135629,0.00003986403,0.0008961504,0.1426502,0.839555,0.002440245,0.0004088121,0.000378847],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2548569,0.00001032247,0.7431332,0.0003213325,0.0004777282,0.0002482687,0.000004364376,0.00003998346,0.0009078453],"genre_scores_gemma":[0.8047773,0.00000394693,0.1943649,0.0004304479,0.00005016072,0.00003680755,0.000008712029,0.000007258142,0.0003204045],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5499204,"threshold_uncertainty_score":0.3657169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02979555764680453,"score_gpt":0.2808632197498939,"score_spread":0.2510676621030894,"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."}}