{"id":"W1549353755","doi":"10.1007/11559573_101","title":"Real Time Head Tracking via Camera Saccade and Shape-Fitting","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor; Simon Fraser University; BC Innovation Council","funders":"","keywords":"Ellipse; Computer vision; Artificial intelligence; Computer science; Saccade; Tracking (education); Kalman filter; Orientation (vector space); Position (finance); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000423989,0.0007146918,0.0008601148,0.0007389784,0.00037061,0.0008979796,0.0008438709,0.0009690163,0.003904636],"category_scores_gemma":[0.001484751,0.0005196403,0.0004436985,0.001173722,0.0002151247,0.0006799472,0.0008539566,0.0005769649,0.002377163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004259023,"about_ca_system_score_gemma":0.0007230758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006027997,"about_ca_topic_score_gemma":0.01163748,"domain_scores_codex":[0.999683,0.00003913074,0.00001293009,0.0001045926,0.0001253373,0.00003502877],"domain_scores_gemma":[0.9995141,0.0001347606,0.00004310293,0.0001188776,0.0001568553,0.00003228682],"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":[0.0009932483,0.00005899661,0.001813439,0.0001483465,0.0001210225,0.0002180117,0.0001680649,0.01491285,0.2251976,0.001670663,0.006351526,0.7483464],"study_design_scores_gemma":[0.0001019319,0.0002720367,0.01272455,0.00003949308,0.0001287822,0.002041385,0.000125342,0.7847984,0.187318,0.003598677,0.008764619,0.00008658704],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03802091,0.0006000415,0.9506578,0.0001193384,0.0001491233,0.00006029018,0.0002902815,0.007072504,0.003029752],"genre_scores_gemma":[0.3630669,0.000475564,0.626096,0.0001590871,0.00006916001,0.00006511931,0.0005285281,0.0006783996,0.008861376],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006027997,"threshold_uncertainty_score":0.0130623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01656306412439335,"score_gpt":0.2787470036476064,"score_spread":0.2621839395232131,"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."}}