{"id":"W2113315588","doi":"10.1109/icpr.2006.602","title":"Generic Real-Time Tracking Method on Semi-Dynamic Scenes","year":2006,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer vision; Computer science; Artificial intelligence; Tracking (education); A priori and a posteriori; Sequence (biology); Track (disk drive); Video tracking; Image (mathematics); Object (grammar)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001233351,0.0002065788,0.0002665438,0.0001604941,0.0001509389,0.0002146408,0.0006859491,0.00008587239,0.00004836616],"category_scores_gemma":[0.00003727915,0.0001734586,0.0001183817,0.0005942341,0.00002394333,0.0003018229,0.0001026321,0.0001275861,0.0002405588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005371756,"about_ca_system_score_gemma":0.00004585351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003101075,"about_ca_topic_score_gemma":0.0000496398,"domain_scores_codex":[0.9980332,0.0003565411,0.0002887287,0.000576388,0.0003215725,0.0004235164],"domain_scores_gemma":[0.9985954,0.0004555817,0.00009526504,0.0007148222,0.00007331079,0.00006562787],"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":[0.00001750667,0.0002740642,0.0037382,0.00003440215,0.00004809369,0.0001225006,0.0001758252,0.01190058,0.1592592,0.08385511,0.002907838,0.7376667],"study_design_scores_gemma":[0.001032919,0.0003009599,0.1254855,0.00008656428,0.0000222278,0.0001483693,0.00001584078,0.7085806,0.09334356,0.06250347,0.007067986,0.001412035],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02642681,0.00007474326,0.9195818,0.0005622869,0.0003082516,0.0001035252,0.000001290998,0.0006686909,0.05227259],"genre_scores_gemma":[0.274672,0.00003032789,0.721563,0.0003393239,0.0001361321,0.000008722378,0.000004638268,0.00002167051,0.003224219],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7362546,"threshold_uncertainty_score":0.7073438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02052737767909437,"score_gpt":0.3087753756377873,"score_spread":0.2882479979586929,"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."}}