{"id":"W2168791921","doi":"10.1109/crv.2007.14","title":"Camera Sensor Model for Visual SLAM","year":2007,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Artificial intelligence; Computer vision; Camera auto-calibration; Computer science; Noise (video); Camera matrix; Camera resectioning; Range (aeronautics); Covariance matrix; Image sensor; Covariance; Gaussian; Pinhole camera model; Calibration; Essential matrix; Gaussian noise; Mathematics; Algorithm; Image (mathematics); Eigenvalues and eigenvectors; Statistics; Engineering","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":[0.00007400839,0.00006870525,0.00006745042,0.00004269694,0.00002697844,0.00001336493,0.00002691484,0.00004990171,0.0000159651],"category_scores_gemma":[0.000008870121,0.00006550294,0.00003235007,0.00004096824,0.000006144882,0.00003189929,0.000003116587,0.00003182869,0.00001459393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002327765,"about_ca_system_score_gemma":0.000004709384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006103838,"about_ca_topic_score_gemma":0.00002583482,"domain_scores_codex":[0.9995741,0.000001403832,0.0001190874,0.00007236578,0.00006132542,0.0001717229],"domain_scores_gemma":[0.9998165,0.00002975178,0.000006512148,0.00006524694,0.0000362201,0.00004571218],"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":[0.000004509908,0.00000761192,0.0000236551,0.00001529862,0.00000679942,7.255575e-7,0.00005918869,0.9892485,0.004068964,0.003474383,0.001058053,0.002032319],"study_design_scores_gemma":[0.0001711866,0.00001397615,0.00003354852,0.000002251764,0.000005122417,7.424963e-7,0.00002335067,0.9906069,0.007960831,0.0001351631,0.0009507338,0.00009617448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03981357,0.00001253688,0.954761,0.00002780016,0.0001111067,0.0001077584,0.000002428628,0.000195202,0.00496865],"genre_scores_gemma":[0.9623867,0.000005856705,0.03545238,0.0001352016,0.00008495335,0.000002653368,0.0000164304,0.00002879092,0.001887013],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9225731,"threshold_uncertainty_score":0.2671132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01443137707593176,"score_gpt":0.2521852091025996,"score_spread":0.2377538320266678,"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."}}