{"id":"W2775646422","doi":"10.1109/iros.2017.8206227","title":"Modular tracking framework: A fast library for high precision tracking","year":2017,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Modular design; BitTorrent tracker; Computer science; Tracking (education); Artificial intelligence; Tracking system; Robotics; Software deployment; Computer vision; Plug-in; Robot; Software engineering; Eye tracking; Kalman filter; Operating system","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":[0.001868298,0.002376695,0.00149161,0.002725378,0.0009549337,0.001936714,0.005066568,0.001946734,0.02749055],"category_scores_gemma":[0.004173269,0.0020219,0.002819374,0.001810176,0.0006641994,0.003217249,0.003584342,0.003216507,0.0283744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001032295,"about_ca_system_score_gemma":0.002100125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004517174,"about_ca_topic_score_gemma":0.005176895,"domain_scores_codex":[0.9985487,0.0001441466,0.0001163904,0.0003365247,0.0006965519,0.0001575471],"domain_scores_gemma":[0.9985217,0.0003342886,0.0001519596,0.0004750686,0.0003968265,0.0001200349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004800156,0.0001519252,0.001442084,0.000844205,0.0002533862,0.0004016918,0.0002922186,0.04539455,0.03134788,0.04028269,0.1787436,0.7003657],"study_design_scores_gemma":[0.0001900869,0.0001975012,0.001300816,0.0002357924,0.0001130594,0.001394102,0.00004727439,0.5155451,0.0605807,0.03070586,0.3893306,0.0003590926],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002682852,0.0001053672,0.9426146,0.00002073439,0.00004538752,0.00004733321,0.0005581379,0.05534066,0.0009994735],"genre_scores_gemma":[0.01308267,0.0003939534,0.9541525,0.0001522926,0.00006690877,0.0004662421,0.006387702,0.01870543,0.006592245],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02749055,"threshold_uncertainty_score":0.09196508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05314091921031202,"score_gpt":0.3307304514092341,"score_spread":0.2775895321989221,"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."}}