{"id":"W1979868736","doi":"10.1007/s00138-008-0138-y","title":"On-line modeling for real-time 3D target tracking","year":2008,"lang":"en","type":"article","venue":"Machine Vision and Applications","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer vision; Computer science; Clutter; Artificial intelligence; Rendezvous; BitTorrent tracker; Object (grammar); Video tracking; A priori and a posteriori; Tracking (education); Line (geometry); Object model; Radar; Engineering; Eye tracking; 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":[0.0002389018,0.0009376986,0.0007649791,0.0004109559,0.0003827731,0.001022831,0.001621068,0.001094431,0.007555631],"category_scores_gemma":[0.0008774645,0.0006697754,0.0008147322,0.0006083635,0.0002314493,0.001086304,0.0007222693,0.0008416217,0.003684688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004908478,"about_ca_system_score_gemma":0.0006237419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01138913,"about_ca_topic_score_gemma":0.01222706,"domain_scores_codex":[0.9997488,0.00004185352,0.0000133863,0.000047841,0.0001218509,0.0000264154],"domain_scores_gemma":[0.9995993,0.0001023105,0.00005115312,0.00009516326,0.0001323427,0.00001973562],"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":[0.0000723725,0.00005081814,0.0003647526,0.00005941509,0.00002837095,0.00007328791,0.00004061193,0.9166209,0.006822916,0.00185051,0.001960625,0.07205546],"study_design_scores_gemma":[0.000001694921,0.000005861504,0.00003455114,0.000001386947,0.000003365163,0.00001115121,0.000002557124,0.9971788,0.001556676,0.0003198109,0.0008820895,0.000002139626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004428499,0.00005198264,0.9910363,0.0000325502,0.00002615684,0.0000187168,0.0001180864,0.002292183,0.001995499],"genre_scores_gemma":[0.5771267,0.0004384296,0.4048097,0.0001549029,0.00004211506,0.0002256155,0.00129747,0.001422683,0.01448238],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01138913,"threshold_uncertainty_score":0.02527612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01962894472129558,"score_gpt":0.2661670980228789,"score_spread":0.2465381533015833,"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."}}