{"id":"W19601591","doi":"10.1021/jp903976z","title":"Pose Estimation of Polygonal Object in Monocular Vision using Parametric Equations of Vertices.","year":2002,"lang":"en","type":"article","venue":"Machine Vision and Applications","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer vision; Artificial intelligence; Polygon (computer graphics); Translation (biology); Rotation (mathematics); Computer science; Object (grammar); Perspective (graphical); Monocular; Monocular vision; Parametric statistics; Pose; Coordinate system; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004452333,0.0009509075,0.00107651,0.001017783,0.000334628,0.001336171,0.001096727,0.001085149,0.002479302],"category_scores_gemma":[0.003065037,0.0008544966,0.0009354095,0.001166326,0.0005798538,0.001303043,0.001582209,0.0009110295,0.0008496532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006992336,"about_ca_system_score_gemma":0.0007918457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01152849,"about_ca_topic_score_gemma":0.01274998,"domain_scores_codex":[0.9995226,0.00009195201,0.00001678059,0.0001657226,0.0001480553,0.0000548969],"domain_scores_gemma":[0.9994173,0.0002408578,0.00009439181,0.00006804054,0.0001254322,0.00005394588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001917809,0.00004447498,0.002517367,0.0001548801,0.00008216963,0.0001526114,0.0001936348,0.6453046,0.006204655,0.006347441,0.002631033,0.3361754],"study_design_scores_gemma":[0.000003362177,0.0000124706,0.0004180195,0.000007843027,0.000003621228,0.00004602742,0.00002899358,0.9966378,0.0005096506,0.001699633,0.0006271311,0.000005510675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03083554,0.0002978965,0.9658546,0.0001160187,0.00004676744,0.00006555472,0.0003061743,0.0007979939,0.001679377],"genre_scores_gemma":[0.5777972,0.0005362467,0.4173834,0.00008996572,0.00004990926,0.0001530608,0.0008710554,0.0001978971,0.002921166],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01152849,"threshold_uncertainty_score":0.02292275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02041433881192029,"score_gpt":0.3219003185099356,"score_spread":0.3014859796980153,"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."}}