{"id":"W4396753389","doi":"10.1109/tim.2024.3398108","title":"Robust Object Pose Tracking for Augmented Reality Guidance and Teleoperation","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Augmented reality; Teleoperation; Pose; Computer vision; Computer science; Artificial intelligence; Object (grammar); Video tracking; Tracking (education); Virtual reality; Telerobotics; Mobile robot; Robot; Psychology","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":[0.0008064974,0.0006671781,0.0005315538,0.0005368001,0.0003485495,0.0009361989,0.0008529063,0.000798189,0.003816368],"category_scores_gemma":[0.003206683,0.0005347364,0.0004686349,0.0006122479,0.0004334697,0.001151294,0.0009724638,0.0007840919,0.002013763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004253699,"about_ca_system_score_gemma":0.000807454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001981559,"about_ca_topic_score_gemma":0.002115885,"domain_scores_codex":[0.9991038,0.0001488875,0.00003447433,0.0001928905,0.0004692631,0.00005068902],"domain_scores_gemma":[0.9990985,0.0002693632,0.0001365008,0.0002364082,0.0002306576,0.00002856841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002853566,0.0000956299,0.00106683,0.0002031841,0.0001002813,0.0001283021,0.0002838724,0.1675955,0.1456417,0.01528729,0.003872606,0.6654394],"study_design_scores_gemma":[0.00003052986,0.0001583845,0.001214315,0.00003185624,0.00003277419,0.000203833,0.00004030341,0.9065607,0.07248915,0.008505228,0.01067427,0.00005869864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002344447,0.00009299328,0.9955758,0.0000206123,0.00002331555,0.00001275646,0.00001783034,0.001421294,0.0004910101],"genre_scores_gemma":[0.2459736,0.0004005087,0.748474,0.00008741271,0.00005490918,0.0001042607,0.000282406,0.0004750041,0.004147877],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003816368,"threshold_uncertainty_score":0.01276702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0948334166498744,"score_gpt":0.2981901215377086,"score_spread":0.2033567048878342,"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."}}