{"id":"W2113192999","doi":"10.1142/s0218001408006399","title":"FACIAL METAMORPHOSIS USING GEOMETRICAL METHODS FOR BIOMETRIC APPLICATIONS","year":2008,"lang":"en","type":"article","venue":"International Journal of Pattern Recognition and Artificial Intelligence","topic":"Face recognition and analysis","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Scheme for Promotion of Academic and Research Collaboration","keywords":"Morphing; Computer science; Computer vision; Biometrics; Artificial intelligence; Face (sociological concept); Facial expression; Expression (computer science); Interpolation (computer graphics); Animation; Feature (linguistics); Computer facial animation; Pattern recognition (psychology); Computer animation; Computer graphics (images); Image (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":[0.0004027696,0.0003278517,0.0003848099,0.0007948769,0.0001971313,0.0005152767,0.0005033413,0.0004714084,0.003730366],"category_scores_gemma":[0.001336284,0.0002894634,0.0006104672,0.0007648464,0.0003991345,0.0007603922,0.0007359704,0.0004420373,0.0009941321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002451424,"about_ca_system_score_gemma":0.000196491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002969817,"about_ca_topic_score_gemma":0.0004106725,"domain_scores_codex":[0.9996263,0.00009826953,0.00002460638,0.0000717185,0.0001623682,0.00001679224],"domain_scores_gemma":[0.9995803,0.0001109582,0.00004557665,0.0001774249,0.0000692482,0.0000165528],"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":[0.0001428432,0.00004707971,0.001510253,0.0002331045,0.00004614758,0.0002237071,0.0002117964,0.06215391,0.1550143,0.02817694,0.002363713,0.7498763],"study_design_scores_gemma":[0.00003115278,0.0001938864,0.00319316,0.00005407828,0.00003786717,0.001615392,0.0001282528,0.8751876,0.06620292,0.02067634,0.03262057,0.00005866408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009236018,0.000372061,0.9879254,0.00008048421,0.00003126913,0.0000297659,0.00003189957,0.0006922611,0.001600929],"genre_scores_gemma":[0.2575677,0.001140977,0.7376021,0.00005001795,0.00005349444,0.00007140164,0.0001650513,0.0001253475,0.003223837],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003730366,"threshold_uncertainty_score":0.01247931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2493129262565186,"score_gpt":0.4159025743362481,"score_spread":0.1665896480797295,"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."}}