{"id":"W1970076768","doi":"10.1109/tmm.2014.2299515","title":"Illumination Robust Video Foreground Prediction Based on Color Recovering","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Foreground detection; Frame (networking); Optical flow; Segmentation; Pixel; Background subtraction; Opacity; Image segmentation; Pattern recognition (psychology); Image (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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004133349,0.0002002852,0.0001514326,0.0003346449,0.0002320541,0.00011532,0.0003893959,0.0001198301,0.00005605911],"category_scores_gemma":[0.00003409455,0.0002052739,0.00009298744,0.0003520798,0.00005473735,0.0007259778,0.000002188172,0.0002588617,0.0001234584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002404972,"about_ca_system_score_gemma":0.00003715355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002660155,"about_ca_topic_score_gemma":0.00003172446,"domain_scores_codex":[0.9984578,0.0001032658,0.000262261,0.0004723032,0.0004299753,0.0002744185],"domain_scores_gemma":[0.9988236,0.000318184,0.00009462137,0.0005735992,0.0001019356,0.00008810462],"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":[0.00009940756,0.0006559099,0.00002006896,0.00004062531,0.00002781011,0.000004789183,0.0005073016,0.217989,0.02277645,0.0002322107,0.001341122,0.7563053],"study_design_scores_gemma":[0.0005058657,0.0004291974,0.0002719588,0.00005630295,0.0000100225,0.000001554788,0.000005494354,0.7983754,0.1991985,0.00005931473,0.0009320847,0.0001543436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004402787,0.000001814529,0.9909461,0.0003458098,0.001448802,0.000423683,0.000012541,0.000916685,0.001501844],"genre_scores_gemma":[0.8166641,0.000006189519,0.182362,0.0003393914,0.00007946095,0.0001923426,0.000006767091,0.00002086938,0.0003289192],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8122613,"threshold_uncertainty_score":0.8370825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01567198960955278,"score_gpt":0.23206444117905,"score_spread":0.2163924515694972,"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."}}