{"id":"W1863704471","doi":"10.1109/iccv.2015.496","title":"FollowMe: Efficient Online Min-Cost Flow Tracking with Bounded Memory and Computation","year":2015,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":116,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computation; Computer science; Bounded function; Online algorithm; Tracking (education); Inference; Minimum-cost flow problem; Algorithm; Mathematical optimization; Flow network; Artificial intelligence; Mathematics","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":[0.001349515,0.001681398,0.001592365,0.001103426,0.0007359557,0.00152343,0.003243892,0.002036577,0.007947695],"category_scores_gemma":[0.005440663,0.0008047792,0.0007765749,0.001652969,0.0007469022,0.003276984,0.001831115,0.001886787,0.002028868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001214128,"about_ca_system_score_gemma":0.002889942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01277256,"about_ca_topic_score_gemma":0.01246035,"domain_scores_codex":[0.9992004,0.0001318443,0.00004117709,0.0002480187,0.0002566845,0.000121788],"domain_scores_gemma":[0.9986765,0.0006982128,0.0001039506,0.0002624077,0.0001964318,0.00006251309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005385044,0.0002793641,0.0009914072,0.000204858,0.00006936564,0.000105465,0.00009884508,0.5178844,0.003948718,0.01859081,0.02365525,0.433633],"study_design_scores_gemma":[0.00002960019,0.00002393214,0.00008945571,0.000005811185,0.000004551912,0.0000234831,0.000007068377,0.9913298,0.0008177974,0.00636679,0.001295703,0.000005980028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00730519,0.0003371752,0.9848422,0.000245265,0.00009468189,0.00008702322,0.0003502782,0.004572777,0.002165361],"genre_scores_gemma":[0.157782,0.0002871972,0.8319566,0.0002471594,0.0001544641,0.0002777155,0.002042782,0.0005397222,0.00671247],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01277256,"threshold_uncertainty_score":0.02658767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06428688319598616,"score_gpt":0.3213269967043053,"score_spread":0.2570401135083191,"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."}}