{"id":"W4408062962","doi":"10.5220/0013153500003905","title":"Silhouette Segmentation for Near-Fall Detection Through Analysis of Human Movements in Surveillance Videos","year":2025,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Silhouette; Segmentation; Computer vision; Artificial intelligence; Computer science; Image segmentation","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":[0.0004029015,0.0009766212,0.001091428,0.003403104,0.0004963488,0.0009057624,0.0007789399,0.0007484051,0.001826119],"category_scores_gemma":[0.001143579,0.0004019405,0.000630524,0.001524939,0.0003194094,0.0005981449,0.0005552079,0.0005481016,0.001296102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004069607,"about_ca_system_score_gemma":0.0005340254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005807629,"about_ca_topic_score_gemma":0.01049876,"domain_scores_codex":[0.9995117,0.00004201771,0.00002193312,0.0001671197,0.0001631209,0.00009410447],"domain_scores_gemma":[0.9995833,0.00009961771,0.00006180552,0.0000432276,0.000159209,0.0000528455],"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":[0.00107346,0.0002814648,0.01250522,0.0003750959,0.0001485109,0.0006181131,0.0003519562,0.02337797,0.2057119,0.00129837,0.007856146,0.7464018],"study_design_scores_gemma":[0.00002049207,0.0002409775,0.03523055,0.00007013841,0.0000892242,0.0008109071,0.0002137556,0.8951015,0.06158959,0.001724537,0.00487205,0.0000362584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1782889,0.00137214,0.812873,0.0001315471,0.0001950689,0.000223892,0.001044548,0.003153266,0.002717635],"genre_scores_gemma":[0.6985607,0.001161094,0.2923966,0.000103649,0.0001598056,0.0001194626,0.002432249,0.0003819871,0.004684565],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005807629,"threshold_uncertainty_score":0.01154768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02555296787024709,"score_gpt":0.3525611330323719,"score_spread":0.3270081651621248,"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."}}