{"id":"W2000731666","doi":"10.1016/j.infrared.2006.06.015","title":"Outdoor infrared video surveillance: A novel dynamic technique for the subtraction of a changing background of IR images","year":2006,"lang":"en","type":"article","venue":"Infrared Physics & Technology","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Background subtraction; Computer science; Infrared; Computer vision; Artificial intelligence; Tracking (education); Miniaturization; Subtraction; Remote sensing; Pixel; Optics","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":[0.0009216108,0.0002500523,0.0004979731,0.0004089573,0.0001559992,0.00004381034,0.001167242,0.0002641782,0.000001881122],"category_scores_gemma":[0.0001095777,0.0002149706,0.0001917366,0.001906956,0.0003125108,0.0003614783,0.0002782076,0.0002969997,0.000001720774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006871419,"about_ca_system_score_gemma":0.0001134989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008006689,"about_ca_topic_score_gemma":0.00002201223,"domain_scores_codex":[0.9982114,0.00006444317,0.0005701145,0.0004448439,0.0002416045,0.0004676013],"domain_scores_gemma":[0.997032,0.0007655105,0.000620483,0.001132781,0.0004286987,0.00002052405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005968333,0.0004612708,0.004280648,0.0002839712,0.0001590663,0.000003839937,0.0002379083,0.0009638678,0.7922562,0.141258,0.0003564941,0.05967902],"study_design_scores_gemma":[0.001226942,0.0002949109,0.01880476,0.0001298005,0.00003180655,0.0000439276,0.0002652402,0.01834893,0.5936369,0.3649335,0.001772245,0.0005111158],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0162374,0.0003394746,0.9811279,0.000494571,0.0002801354,0.0007158375,0.00006951336,0.000315062,0.0004200714],"genre_scores_gemma":[0.8543878,0.00002742,0.1450588,0.00003353393,0.00006647586,0.0002852125,0.00001441661,0.0000272471,0.00009909346],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8381504,"threshold_uncertainty_score":0.8766247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01730625962544621,"score_gpt":0.2879637601511505,"score_spread":0.2706575005257044,"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."}}