{"id":"W2139086897","doi":"10.1109/svr.2011.35","title":"Real-Time Estimation of Missing Markers for Reconstruction of Human Motion","year":2011,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Extrapolation; Computer science; Motion capture; Artificial intelligence; Computer vision; Motion (physics); Missing data; Match moving; Kalman filter; Motion estimation; Structure from motion; Solver; Tracking (education); Position (finance); Mathematics; Machine learning","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":[0.0004530892,0.0005449714,0.0005039114,0.0005090294,0.0002470877,0.0003432799,0.0005174182,0.0006007805,0.001213152],"category_scores_gemma":[0.001966676,0.0003711255,0.0003838128,0.000478409,0.0003467847,0.0006243513,0.0005642519,0.0006484421,0.0003819125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00021658,"about_ca_system_score_gemma":0.0005027798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002031665,"about_ca_topic_score_gemma":0.003180979,"domain_scores_codex":[0.9997364,0.00007243989,0.0000134025,0.0000604478,0.00009786862,0.00001954489],"domain_scores_gemma":[0.999557,0.0001493473,0.00007140214,0.0001174581,0.00007816737,0.00002668027],"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":[0.0004878617,0.00007875107,0.002951515,0.0002690601,0.00008560798,0.0003725964,0.0004444777,0.3226364,0.1209817,0.007914446,0.00297865,0.5407989],"study_design_scores_gemma":[0.00001224988,0.00004693626,0.0009142427,0.00001657084,0.0000154234,0.0002607708,0.00004020108,0.9689779,0.02566619,0.001720658,0.002309904,0.00001899722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008957378,0.0001068661,0.9903107,0.00003565859,0.00001898643,0.000008619122,0.0000260099,0.0003552182,0.0001805798],"genre_scores_gemma":[0.3296555,0.0003781503,0.6681046,0.0000398064,0.00002691725,0.00003593373,0.0001814123,0.0001205798,0.00145708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002031665,"threshold_uncertainty_score":0.004058421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02652781186032327,"score_gpt":0.2368913153660596,"score_spread":0.2103635035057363,"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."}}