{"id":"W2130288511","doi":"10.1109/ccece.2007.334","title":"Face Recognition Under Significant Pose Variation","year":2007,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Artificial intelligence; Computer science; Facial recognition system; Computer vision; Face (sociological concept); Pattern recognition (psychology); AdaBoost; Three-dimensional face recognition; Pose; Face detection; Active appearance model; Variation (astronomy); Image (mathematics); Support vector machine","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":[0.0005762543,0.0004275762,0.001002003,0.0004982048,0.0002726571,0.0005739286,0.000472639,0.0006158773,0.001194159],"category_scores_gemma":[0.001540249,0.0002015238,0.0004271413,0.000430855,0.000358659,0.0006639061,0.0005628815,0.0004070045,0.0007005549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002462202,"about_ca_system_score_gemma":0.0002429624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008647199,"about_ca_topic_score_gemma":0.0007467282,"domain_scores_codex":[0.9990502,0.0001191441,0.00002959552,0.0002724597,0.0003892925,0.0001392605],"domain_scores_gemma":[0.9995004,0.0001450754,0.00007233533,0.0001224397,0.0001354406,0.00002424171],"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":[0.0005715129,0.0001236036,0.007341682,0.0001021328,0.0001114234,0.0008684949,0.0001575055,0.05305637,0.2775584,0.002395068,0.002823296,0.6548905],"study_design_scores_gemma":[0.00002378717,0.0004214278,0.03067353,0.00001482342,0.00006925085,0.003410235,0.0001793365,0.8212513,0.1345228,0.005842353,0.003532198,0.00005899914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4105202,0.001109859,0.5809858,0.0002712714,0.0002283422,0.00006235587,0.0002421713,0.001502484,0.005077437],"genre_scores_gemma":[0.9460778,0.0004124136,0.04914949,0.0001207285,0.0001261215,0.00004449078,0.0003898942,0.00007349434,0.003605634],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001194159,"threshold_uncertainty_score":0.003994823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02839435131818251,"score_gpt":0.2534785585854878,"score_spread":0.2250842072673053,"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."}}