{"id":"W2080466697","doi":"10.1145/2546276","title":"Facial performance enhancement using dynamic shape space analysis","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Motion capture; Animation; Artificial intelligence; Computer facial animation; Computer vision; Computer graphics (images); Computer animation; Facial motion capture; Motion (physics); Pattern recognition (psychology); Facial recognition system; Face detection","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":[0.0003392722,0.0007330928,0.0004783551,0.0009339067,0.0002639093,0.0007090789,0.0005434347,0.0003524077,0.004731833],"category_scores_gemma":[0.001127671,0.0002680365,0.0006443138,0.0004180631,0.0003511166,0.0005532262,0.001036022,0.0005725826,0.001352421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000358104,"about_ca_system_score_gemma":0.0002823058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001471787,"about_ca_topic_score_gemma":0.002225444,"domain_scores_codex":[0.999669,0.00004198425,0.00001016698,0.00006503914,0.0001776865,0.00003620961],"domain_scores_gemma":[0.9996796,0.00009160268,0.0000346442,0.00008218262,0.00008404395,0.00002797744],"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":[0.0002770751,0.0001011284,0.001981402,0.0001683067,0.00007168709,0.0002349976,0.0002763535,0.09632045,0.2711304,0.003580385,0.005188904,0.6206689],"study_design_scores_gemma":[0.0000192233,0.0001922408,0.005891529,0.00004311985,0.00004807661,0.0008188362,0.0001788337,0.8765718,0.09865376,0.003295551,0.01422014,0.00006680719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08960868,0.0002751694,0.8950058,0.0002026273,0.00008166343,0.0001204897,0.0002979087,0.004662448,0.00974525],"genre_scores_gemma":[0.5959643,0.0005893933,0.3920019,0.0001656778,0.00007332505,0.00009785727,0.0008856393,0.0009812515,0.0092407],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004731833,"threshold_uncertainty_score":0.01582956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0144826579972289,"score_gpt":0.2346707235617123,"score_spread":0.2201880655644834,"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."}}