{"id":"W3021986634","doi":"","title":"Pan-tilt-zoom SLAM for Sports Videos","year":2019,"lang":"en","type":"article","venue":"British Machine Vision Conference","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Zoom; Tilt (camera); Simultaneous localization and mapping; Tracking (education); Rotation (mathematics); Track (disk drive); Computer graphics (images); Robot; Mobile robot; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003570239,0.001203379,0.0009898635,0.001087,0.0006053154,0.0006039091,0.001003319,0.0005733146,0.00472755],"category_scores_gemma":[0.001292434,0.0005714453,0.0005056192,0.001066721,0.0003055667,0.0009184753,0.001150574,0.0009960524,0.001969238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003241934,"about_ca_system_score_gemma":0.0008701957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01143151,"about_ca_topic_score_gemma":0.02090871,"domain_scores_codex":[0.9995624,0.00006047343,0.00001470678,0.0001329957,0.0001495067,0.00007986597],"domain_scores_gemma":[0.9996878,0.00005147625,0.00003913228,0.00009806717,0.00009063635,0.00003290388],"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":[0.0004653787,0.0001920078,0.001763112,0.0002730424,0.0001214364,0.0002369122,0.0001538499,0.07921459,0.05821006,0.00191311,0.01891469,0.8385419],"study_design_scores_gemma":[0.00009445043,0.0002598736,0.004524676,0.00004776515,0.0000246201,0.0003046685,0.0001345581,0.9503422,0.02653792,0.00500791,0.01267728,0.00004399383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02512667,0.0003954961,0.9619057,0.00008034929,0.0001595066,0.0001153719,0.0006885661,0.008924617,0.002603745],"genre_scores_gemma":[0.4946298,0.000437392,0.496206,0.0002197964,0.0001376193,0.000201698,0.002516223,0.0005942493,0.005057194],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01143151,"threshold_uncertainty_score":0.02272993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006370585020681912,"score_gpt":0.2175587545470391,"score_spread":0.2111881695263572,"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."}}