{"id":"W2052524720","doi":"10.1109/cvprw.2012.6238919","title":"Changedetection.net: A new change detection benchmark dataset","year":2012,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":814,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Benchmarking; Benchmark (surveying); Change detection; Artificial intelligence; Ranking (information retrieval); Ground truth; Frame (networking); Shadow (psychology); Machine learning; Data mining; Information retrieval","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001816936,0.002569262,0.001368853,0.005743756,0.001331951,0.002072573,0.004490034,0.002600093,0.003850404],"category_scores_gemma":[0.005438929,0.0005298521,0.001634596,0.005392083,0.0007854062,0.002333462,0.002030457,0.002271286,0.005118283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001963134,"about_ca_system_score_gemma":0.001522364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02453094,"about_ca_topic_score_gemma":0.04013817,"domain_scores_codex":[0.9976357,0.0002714732,0.0003166992,0.0006573522,0.000881334,0.0002373965],"domain_scores_gemma":[0.9967713,0.000564692,0.0003834415,0.0008912994,0.001062777,0.0003265346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001305556,0.001410128,0.01741265,0.002201516,0.000426417,0.0006690614,0.0002134368,0.02471766,0.01316825,0.003052017,0.7610869,0.1743366],"study_design_scores_gemma":[0.0009619825,0.001060114,0.1064875,0.0004755283,0.0003490059,0.002942704,0.0006813623,0.1827395,0.03482057,0.005571216,0.6634858,0.0004247367],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.08732125,0.003512428,0.03053307,0.001295861,0.001284507,0.001754172,0.8355939,0.02403829,0.0146666],"genre_scores_gemma":[0.02522989,0.0003371966,0.02125002,0.0001755879,0.00008748758,0.0005864868,0.949928,0.0004190143,0.001986288],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02453094,"threshold_uncertainty_score":0.04877633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09362766237507576,"score_gpt":0.3200240891011569,"score_spread":0.2263964267260811,"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."}}