{"id":"W1533704302","doi":"10.1007/978-3-642-10467-1_32","title":"Automatic Detection of Object of Interest and Tracking in Active Video","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Artificial intelligence; Initialization; Computer vision; Video tracking; AdaBoost; Classifier (UML); Pattern recognition (psychology); Object detection; Salient; Object (grammar)","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":[0.0005900833,0.0006011346,0.0007645179,0.001403569,0.0002801159,0.001058169,0.001540752,0.00110466,0.001498307],"category_scores_gemma":[0.001325202,0.0005628845,0.0004949664,0.0009817288,0.0004048701,0.00113291,0.0006853643,0.0006319468,0.001200373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002369091,"about_ca_system_score_gemma":0.0002396743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001015785,"about_ca_topic_score_gemma":0.001476944,"domain_scores_codex":[0.9996268,0.00003209406,0.00001508666,0.0001173952,0.0001586492,0.00004994175],"domain_scores_gemma":[0.999361,0.0002870606,0.00005576993,0.00009373516,0.0001670002,0.00003547164],"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":[0.0002161665,0.0001144746,0.0009175937,0.0001717835,0.00003586286,0.0001283862,0.00009769923,0.00717053,0.1790914,0.004247495,0.002891021,0.8049177],"study_design_scores_gemma":[0.00003389097,0.0002507569,0.00724564,0.00006290782,0.000121967,0.001424239,0.00007759682,0.6890517,0.2779967,0.009462325,0.01421592,0.00005628661],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02514245,0.001165759,0.9696857,0.00004911372,0.0001274551,0.00004415813,0.00009923043,0.001096651,0.002589377],"genre_scores_gemma":[0.2921269,0.001711405,0.6929374,0.0001261295,0.0001538921,0.00008234376,0.0006792647,0.0002849317,0.0118977],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001540752,"threshold_uncertainty_score":0.005012333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03684155327446538,"score_gpt":0.2962240426561342,"score_spread":0.2593824893816688,"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."}}