{"id":"W2066021222","doi":"10.1109/tii.2013.2294134","title":"Gaussian Mixture Model With Advanced Distance Measure Based on Support Weights and Histogram of Gradients for Background Suppression","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Informatics","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Mixture model; Histogram; Pattern recognition (psychology); Artificial intelligence; Computer science; Measure (data warehouse); Foreground detection; Pixel; Noise (video); Generalization; Background subtraction; Object detection; Mathematics; Computer vision; Image (mathematics); Data mining","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":[0.0009782894,0.0009722308,0.0009316119,0.001223773,0.0003020813,0.0008599132,0.001306653,0.0008966462,0.0008982748],"category_scores_gemma":[0.001905181,0.0003506802,0.001080288,0.001397548,0.0004010983,0.001648751,0.0008410356,0.001326936,0.0007093435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004947053,"about_ca_system_score_gemma":0.0008059649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005041105,"about_ca_topic_score_gemma":0.003557805,"domain_scores_codex":[0.9992399,0.000164122,0.00003445917,0.0001771424,0.0003162989,0.00006818461],"domain_scores_gemma":[0.9996141,0.0001270523,0.00003669415,0.00005158267,0.0001478756,0.00002270925],"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":[0.000342296,0.0001861324,0.003522778,0.0002979515,0.0002515604,0.0001954716,0.0002264475,0.2857707,0.04388668,0.03495139,0.004383956,0.6259846],"study_design_scores_gemma":[0.000006477625,0.00004767339,0.000612199,0.00000825715,0.00003107322,0.00009181123,0.00001495065,0.9886914,0.005509428,0.002856741,0.002105063,0.00002486815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00710576,0.0004357407,0.9914861,0.00005436776,0.00004506391,0.00001892172,0.00002135248,0.0003488954,0.0004836893],"genre_scores_gemma":[0.3764406,0.001786468,0.614876,0.0001414071,0.0001430052,0.0001315205,0.0004293582,0.000245492,0.005806087],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005041105,"threshold_uncertainty_score":0.01002347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04100685308295286,"score_gpt":0.2748817309567324,"score_spread":0.2338748778737795,"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."}}