{"id":"W1561770131","doi":"","title":"Automated person segmentation in videos","year":2012,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Artificial intelligence; Conditional random field; Computer vision; Computer science; Segmentation; Pose; Detector; Frame (networking); Image segmentation; Optical flow; 3D pose estimation; Pattern recognition (psychology); Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001842623,0.0002457386,0.0002738487,0.0004987132,0.0001321345,0.0001902244,0.0006602459,0.0001844039,0.00001350401],"category_scores_gemma":[0.0001844492,0.0002490871,0.000103016,0.0009928677,0.00003322591,0.001416618,0.0001416436,0.0002971039,0.00004460842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003997596,"about_ca_system_score_gemma":0.0001006776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003180025,"about_ca_topic_score_gemma":0.0007344538,"domain_scores_codex":[0.9977248,0.000369103,0.0003449176,0.0003674987,0.0003364916,0.0008571669],"domain_scores_gemma":[0.9986382,0.0001877801,0.0001572498,0.0007213424,0.00005615299,0.0002392395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003124432,0.0004599886,0.7255223,0.00004691939,0.00003747152,0.00005921499,0.003257342,0.001941662,0.02420917,0.03680543,0.002217442,0.2054118],"study_design_scores_gemma":[0.0005130821,0.00008045949,0.6230405,0.00004351127,0.000006728218,0.00009344043,0.0001213643,0.3552425,0.01899402,0.0007880436,0.0006638546,0.0004125234],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1456599,0.0009334363,0.8480954,0.001817921,0.000290744,0.0004027861,0.0000038948,0.002162258,0.000633592],"genre_scores_gemma":[0.6610018,0.00002918823,0.3376099,0.001007609,0.00007553231,0.0001614385,0.000006069126,0.00002080862,0.00008768291],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5153419,"threshold_uncertainty_score":0.9999961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02125994655324343,"score_gpt":0.2797878230200291,"score_spread":0.2585278764667857,"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."}}