{"id":"W1499997787","doi":"10.1109/ccece.2015.7129491","title":"Visual tracking based on compressive sensing and particle filter","year":2015,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Particle filter; Robustness (evolution); Artificial intelligence; Computer science; Computer vision; Active appearance model; Tracking (education); Compressed sensing; Eye tracking; Classifier (UML); Pattern recognition (psychology); Filter (signal processing); 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":[0.0006552219,0.0005590242,0.0007539971,0.0007288238,0.0004026618,0.0006272114,0.0007917854,0.0009200436,0.0006462307],"category_scores_gemma":[0.002463466,0.0003409176,0.0006780405,0.0008476389,0.0005629188,0.001122191,0.0007629422,0.0008293379,0.000233282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005097521,"about_ca_system_score_gemma":0.0007160157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005106692,"about_ca_topic_score_gemma":0.003052437,"domain_scores_codex":[0.9994116,0.00008633642,0.00003352574,0.0001480249,0.0002833925,0.00003715961],"domain_scores_gemma":[0.9993424,0.0002779193,0.000102115,0.00007525596,0.0001666407,0.00003568447],"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":[0.0001667422,0.0001270394,0.001574134,0.000192277,0.0001081192,0.0002222698,0.0001856356,0.4812556,0.04368351,0.03664099,0.003486363,0.4323573],"study_design_scores_gemma":[0.000009238388,0.00003393339,0.0002355309,0.000006018618,0.000007713039,0.00007380973,0.000005219082,0.9938639,0.002317016,0.00257496,0.0008603766,0.0000122084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003739873,0.0002263535,0.9947647,0.00008550091,0.00005641647,0.00002049802,0.00001164993,0.0001748524,0.0009201994],"genre_scores_gemma":[0.4407479,0.001245267,0.5536434,0.0002710183,0.0002769608,0.0001773408,0.0001793907,0.00005365573,0.003405101],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005106692,"threshold_uncertainty_score":0.01015395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07694932452341158,"score_gpt":0.3353905339871005,"score_spread":0.2584412094636889,"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."}}