{"id":"W1614841168","doi":"","title":"Crowd analysis with target tracking, K-means clustering and hidden Markov models","year":2012,"lang":"en","type":"article","venue":"International Conference on Information Fusion","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National d'Optique","funders":"","keywords":"Crowds; Hidden Markov model; Cluster analysis; Centroid; Computer science; Tracking (education); Artificial intelligence; Pattern recognition (psychology); Crowd psychology; Markov chain; k-means clustering; Data mining; 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":[0.002310736,0.001286867,0.001440642,0.002529877,0.001140579,0.001537148,0.001441428,0.001316202,0.0007510168],"category_scores_gemma":[0.006055401,0.0008860852,0.001590431,0.002149123,0.001143042,0.00180665,0.001800108,0.001233304,0.0006067632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001472357,"about_ca_system_score_gemma":0.00160278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02110635,"about_ca_topic_score_gemma":0.01267202,"domain_scores_codex":[0.9984579,0.0006044456,0.00007688878,0.0003397703,0.000413532,0.0001075432],"domain_scores_gemma":[0.9978443,0.001273181,0.0003116341,0.0001846214,0.0003051173,0.00008113947],"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":[0.0001030229,0.00005684983,0.002111884,0.0001321508,0.0001678152,0.0001154292,0.0003271344,0.88251,0.00163346,0.01890066,0.001789144,0.09215245],"study_design_scores_gemma":[0.000003433438,0.000009975398,0.0003202395,0.000009571579,0.000009972773,0.00002138414,0.00002856502,0.9851369,0.0004743143,0.01333851,0.0006310879,0.00001601295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006363909,0.000333808,0.9920347,0.00009928901,0.00003500963,0.00004305199,0.00005820097,0.0004057996,0.0006262417],"genre_scores_gemma":[0.3762168,0.001025362,0.6177942,0.0001223884,0.000231571,0.0002540661,0.00057304,0.0001958902,0.003586811],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02110635,"threshold_uncertainty_score":0.04196703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02469062103090949,"score_gpt":0.2624692680882453,"score_spread":0.2377786470573358,"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."}}