{"id":"W2117876688","doi":"10.1109/crv.2011.33","title":"Autocalibration: Finding Infinity in a Projective Reconstruction","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Ontario Centres of Excellence","keywords":"Initialization; Intrinsics; Computer science; Mathematical optimization; Calibration; Measure (data warehouse); Metric (unit); Affine transformation; Algorithm; Nonlinear programming; Artificial intelligence; Nonlinear system; Computer vision; Mathematics; Data mining","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001630869,0.0008241851,0.0009406203,0.0008849343,0.0007119318,0.001010971,0.001002091,0.00109432,0.002360065],"category_scores_gemma":[0.004492861,0.000510959,0.0007160958,0.0006051758,0.001363022,0.001970215,0.002167964,0.001012722,0.0006724829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005210479,"about_ca_system_score_gemma":0.0009698974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002043031,"about_ca_topic_score_gemma":0.002117203,"domain_scores_codex":[0.9990675,0.0002857364,0.00003917691,0.0002264547,0.000316263,0.00006493885],"domain_scores_gemma":[0.998645,0.0006554165,0.0001491673,0.000290642,0.0002112787,0.00004850556],"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":[0.0001961643,0.0001083526,0.003076844,0.0001454976,0.00009596418,0.0002349709,0.0005682648,0.5006749,0.02566396,0.04465101,0.00132654,0.4232575],"study_design_scores_gemma":[0.00002201346,0.0001638358,0.0007030718,0.000024538,0.00002016159,0.0002564406,0.00009112385,0.959141,0.01940788,0.0176489,0.002489731,0.00003132263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04424306,0.0000913966,0.9525877,0.00008398774,0.00001004815,0.00003820529,0.00002542355,0.0006260459,0.002294106],"genre_scores_gemma":[0.366706,0.0001097006,0.6302884,0.0000811625,0.00001499964,0.00007487422,0.0001428661,0.0002241468,0.002357897],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002360065,"threshold_uncertainty_score":0.008624971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.070294656755985,"score_gpt":0.2820358966800328,"score_spread":0.2117412399240478,"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."}}