{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003564621,0.0008347665,0.0007247874,0.0009260181,0.0004081064,0.0005957002,0.0009217146,0.0004415487,0.0006982936],"category_scores_gemma":[0.001460997,0.0002932736,0.000493209,0.0007073319,0.0004063274,0.001071273,0.000545723,0.000745485,0.0004570675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004630096,"about_ca_system_score_gemma":0.0006462048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004939525,"about_ca_topic_score_gemma":0.00345366,"domain_scores_codex":[0.9997105,0.00002499099,0.00001204014,0.00009813834,0.0001159688,0.00003833376],"domain_scores_gemma":[0.9995062,0.000123111,0.00008864149,0.00009222856,0.0001600106,0.00002978337],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004898233,0.00008367359,0.002438794,0.0001021153,0.00005416058,0.0002570237,0.0001526552,0.1013534,0.1423893,0.003080695,0.002207155,0.7473913],"study_design_scores_gemma":[0.00001058887,0.00004678982,0.0009781684,0.000009133936,0.00002476505,0.0001772337,0.000017589,0.9299361,0.06687761,0.0009607756,0.0009391491,0.00002211772],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02746707,0.0003184937,0.9698238,0.00004679431,0.00003593844,0.00003787944,0.00004591313,0.001551888,0.00067238],"genre_scores_gemma":[0.4954334,0.0007006376,0.5013783,0.00008165124,0.00008288456,0.00005326749,0.0002975281,0.0001941713,0.001778175],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004939525,"threshold_uncertainty_score":0.009821534,"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."}}