{"id":"W2037736748","doi":"10.5402/2012/672084","title":"Model-Free, Occlusion Accommodating Active Contour Tracking","year":2012,"lang":"en","type":"article","venue":"ISRN Artificial Intelligence","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; University of Alberta","funders":"","keywords":"Computer vision; Artificial intelligence; Tracking (education); Clutter; Active contour model; Term (time); Frame (networking); Kernel (algebra); Computer science; Mathematics; Set (abstract data type); Active appearance model; Image (mathematics); Image segmentation; Radar; Physics","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":[0.001070694,0.0006609814,0.0009193679,0.0004762564,0.0003185527,0.0008332402,0.001175393,0.001001098,0.0006266333],"category_scores_gemma":[0.002720734,0.0005248532,0.000497858,0.0006854734,0.0006362179,0.001288453,0.0008704927,0.0006473526,0.0002993799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006204812,"about_ca_system_score_gemma":0.0006936272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002622753,"about_ca_topic_score_gemma":0.002682283,"domain_scores_codex":[0.9995529,0.00009826296,0.00001564245,0.00009455103,0.0002016725,0.00003691907],"domain_scores_gemma":[0.9993438,0.0002978733,0.0001113409,0.0001287187,0.00009003845,0.00002812902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001415376,0.00007874162,0.0009020125,0.0001185619,0.00006760289,0.000139585,0.000238266,0.7036686,0.04115269,0.0155971,0.0009505039,0.2369448],"study_design_scores_gemma":[0.000003195953,0.00001552052,0.0001447929,0.000002541476,0.000004004851,0.00002899514,0.000003745238,0.995397,0.002672801,0.001206293,0.0005164021,0.000004668925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01067049,0.0001137357,0.9884216,0.00002748624,0.00001010185,0.00001347176,0.00001184855,0.0001604845,0.0005707727],"genre_scores_gemma":[0.437281,0.0002894027,0.5586031,0.00007995882,0.00004017439,0.00009953409,0.0001302865,0.0001561517,0.00332044],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002622753,"threshold_uncertainty_score":0.005662441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1030764168476395,"score_gpt":0.3579710233625648,"score_spread":0.2548946065149252,"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."}}