{"id":"W1982838549","doi":"10.1504/ijamc.2009.026854","title":"Human Computer interaction for smart environment applications using hand gestures and facial expressions","year":2009,"lang":"en","type":"article","venue":"International Journal of Advanced Media and Communication","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada; Innovation, Science and Economic Development Canada; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gesture; Computer science; Modalities; Facial expression; Human–computer interaction; Gesture recognition; Body language; Multimedia; Artificial intelligence; Communication","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0005843424,0.000597771,0.0003876086,0.0003507412,0.0002980315,0.001037264,0.0004089378,0.0008457856,0.007135296],"category_scores_gemma":[0.001429861,0.000141609,0.0003200742,0.0003875251,0.0004783949,0.001253625,0.001031651,0.0003090556,0.002598841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002345241,"about_ca_system_score_gemma":0.0002080937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009862361,"about_ca_topic_score_gemma":0.00184665,"domain_scores_codex":[0.999359,0.0001879016,0.00003255219,0.0001042141,0.000255397,0.00006094875],"domain_scores_gemma":[0.9998088,0.00008843971,0.00002245552,0.00002758774,0.00003795019,0.00001488307],"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":[0.0003986709,0.00008488558,0.001876847,0.0007722403,0.00007016896,0.0004191916,0.0009657618,0.00387512,0.2889027,0.0128224,0.01661574,0.6731963],"study_design_scores_gemma":[0.0001305632,0.001616107,0.0559614,0.001024895,0.0003793475,0.006002934,0.002001606,0.1694831,0.2856013,0.03674056,0.4405496,0.0005086364],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09160648,0.01236175,0.8060569,0.001882406,0.0008109568,0.0004168711,0.0003978973,0.004336312,0.08213037],"genre_scores_gemma":[0.7088676,0.006840326,0.2435303,0.0008816611,0.000265883,0.0003901244,0.000422491,0.0003446082,0.03845709],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007135296,"threshold_uncertainty_score":0.02386999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02776568103470938,"score_gpt":0.3207385145330162,"score_spread":0.2929728334983068,"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."}}