{"id":"W2095275517","doi":"10.1142/s0218001403002563","title":"ACTIVE HEAD TRACKING BASED ON CHROMATIC SHAPE FITTING","year":2003,"lang":"en","type":"article","venue":"International Journal of Pattern Recognition and Artificial Intelligence","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; BC Innovation Council","funders":"","keywords":"Computer vision; Artificial intelligence; Ellipse; Computer science; Chromatic scale; Centroid; Saccade; Tracking (education); Position (finance); Orientation (vector space); Foveal; Mathematics; Eye movement; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008546596,0.0001259496,0.0001657591,0.0002661697,0.00007896728,0.0002819693,0.0003789946,0.00004801815,0.0003450461],"category_scores_gemma":[0.0007114455,0.0001139097,0.0001041338,0.00014797,0.00003456921,0.0004909546,0.00002439519,0.0002393291,0.00008473272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004455945,"about_ca_system_score_gemma":0.00006323487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005042869,"about_ca_topic_score_gemma":0.000008036172,"domain_scores_codex":[0.9984264,0.000236719,0.0005336727,0.0001985983,0.0004501463,0.0001544771],"domain_scores_gemma":[0.9983037,0.0006002575,0.0004075022,0.0001013799,0.0005031973,0.00008395007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000238883,0.0001115358,0.0004423027,0.000006687876,0.00002760214,0.00007376126,0.0003022481,0.0002744607,0.0006961531,0.0004269585,0.000007869824,0.9976065],"study_design_scores_gemma":[0.0006680051,0.001149058,0.0115258,0.002671593,0.00003715478,0.0009130117,0.0008391255,0.3922758,0.4295051,0.1583817,0.001099268,0.0009344299],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.179502,0.00002813361,0.8178033,0.0008965709,0.00110006,0.00005902529,0.00001400317,0.00001925115,0.0005776832],"genre_scores_gemma":[0.9850425,0.00002228668,0.01362209,0.001102948,0.0001925398,0.000002708645,0.000004145,0.00000772263,0.000003111965],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9966721,"threshold_uncertainty_score":0.4645101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1488864731902557,"score_gpt":0.3664002233785071,"score_spread":0.2175137501882514,"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."}}