{"id":"W2097973940","doi":"10.1109/cvprw.2010.5543510","title":"Feedback scheme for thermal-visible video registration, sensor fusion, and people tracking","year":2010,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Computer vision; Artificial intelligence; RANSAC; Computer science; Tracking (education); Trajectory; Affine transformation; Video tracking; Sensor fusion; Transformation (genetics); Matching (statistics); Geometric transformation; Image registration; Pixel; Fusion; Object (grammar); Image (mathematics); Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001446831,0.0008370947,0.0008494452,0.0005040673,0.0007244046,0.0004812204,0.001943551,0.001203623,0.002355307],"category_scores_gemma":[0.003614016,0.0004366153,0.0004559091,0.0004613299,0.0007371124,0.001616048,0.001345442,0.0009981523,0.0006352275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000678174,"about_ca_system_score_gemma":0.0006406863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002094824,"about_ca_topic_score_gemma":0.002654868,"domain_scores_codex":[0.9986196,0.0002515214,0.00007585519,0.0003632572,0.0005890941,0.0001006283],"domain_scores_gemma":[0.9986026,0.0004424066,0.0002146917,0.0002368497,0.0004223837,0.00008123311],"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":[0.001182579,0.0003722399,0.0009478228,0.0002996303,0.0000930024,0.0002593313,0.0005513572,0.1330744,0.1723359,0.01427641,0.003794015,0.6728132],"study_design_scores_gemma":[0.00008590428,0.0003736096,0.0005978752,0.00001700811,0.00003265239,0.0002083688,0.00003266254,0.9468109,0.04482688,0.003813216,0.003143948,0.00005690557],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005966904,0.00009581337,0.993028,0.00004299017,0.00005229087,0.00003235291,0.00001092755,0.000502211,0.0002685218],"genre_scores_gemma":[0.5370997,0.0001835432,0.4583204,0.0001759782,0.000137116,0.0002554056,0.00008307108,0.000093774,0.003650938],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002355307,"threshold_uncertainty_score":0.007879317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02357341140208377,"score_gpt":0.2900518469937685,"score_spread":0.2664784355916847,"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."}}