{"id":"W4309505594","doi":"10.1145/3562939.3565660","title":"LivePose: Democratizing Pose Detection for Multimedia Arts and Telepresence Applications on Open Edge Devices","year":2022,"lang":"en","type":"article","venue":"","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Society for Arts and Technology","funders":"","keywords":"Computer science; Pipeline (software); Frame (networking); Enhanced Data Rates for GSM Evolution; Multimedia; License; Telerobotics; Computer graphics (images); Computer vision; Artificial intelligence; Computer network; Robot; Operating system","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":[0.000577623,0.001795172,0.0007146986,0.001036995,0.0004430541,0.00146024,0.002152875,0.0007673564,0.02506346],"category_scores_gemma":[0.002536192,0.0008262497,0.0009904263,0.0004728988,0.0006623637,0.001975958,0.002726921,0.001148479,0.006959151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004721865,"about_ca_system_score_gemma":0.0005994627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002446324,"about_ca_topic_score_gemma":0.005240214,"domain_scores_codex":[0.9993008,0.00004690976,0.00002359271,0.0002016632,0.0003271185,0.00009988537],"domain_scores_gemma":[0.9994193,0.0001935114,0.00003623946,0.000165329,0.0001139743,0.00007163476],"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":[0.001740906,0.0003702584,0.00635542,0.0005153448,0.0003268956,0.0007050152,0.0006913374,0.02747975,0.1637838,0.01095837,0.1630709,0.624002],"study_design_scores_gemma":[0.0003120477,0.0005061732,0.00846645,0.0001184117,0.000115497,0.0008803973,0.0002483398,0.5591328,0.3055543,0.01426972,0.1101293,0.0002665761],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01873652,0.0002044525,0.8065409,0.0001963045,0.0002245985,0.000250788,0.002444353,0.1633229,0.008079107],"genre_scores_gemma":[0.3229371,0.0004139375,0.6155221,0.0009273643,0.0002662685,0.000641329,0.01143507,0.02923329,0.01862357],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02506346,"threshold_uncertainty_score":0.08384562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04156741144858709,"score_gpt":0.3020976270025967,"score_spread":0.2605302155540096,"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."}}