{"id":"W7071889742","doi":"","title":"Temporal Motion Models for Monocular and Multiview 3âD Human Body Tracking","year":2006,"lang":"en","type":"article","venue":"Infoscience (Ecole Polytechnique Fédérale de Lausanne)","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Tracking (education); Monocular; Motion (physics); Minification; Generality; Differential (mechanical device); Trajectory; Match moving","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004265873,0.0004526465,0.0005758881,0.0005544329,0.0002696567,0.0006316632,0.0007915685,0.0007208618,0.002367088],"category_scores_gemma":[0.001522753,0.0004971045,0.0006560595,0.0008845503,0.0002553904,0.0007297877,0.0005623681,0.0006257617,0.00115442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004703045,"about_ca_system_score_gemma":0.000610375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01330268,"about_ca_topic_score_gemma":0.01924,"domain_scores_codex":[0.9998444,0.00002338203,0.000009603928,0.00004727657,0.00005194094,0.00002331376],"domain_scores_gemma":[0.9997781,0.00007356372,0.00003788238,0.00003729219,0.00005775195,0.00001530896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002430175,0.00006557729,0.001635558,0.00008232557,0.00006115851,0.00006982537,0.00006931304,0.8276848,0.008656404,0.008468569,0.001948706,0.1510148],"study_design_scores_gemma":[0.000002936206,0.000008790236,0.0003091699,0.000003573776,0.000005162115,0.00001964172,0.000003540383,0.9974852,0.0004581808,0.001299558,0.0004010558,0.00000318198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01846296,0.0004965744,0.9788054,0.00009353463,0.00005927894,0.00002039716,0.0003830785,0.0004923474,0.00118643],"genre_scores_gemma":[0.8570858,0.0009835849,0.1319527,0.0001143096,0.00007109298,0.0001553436,0.001263796,0.000210609,0.008162823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01330268,"threshold_uncertainty_score":0.02645051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02305060243779342,"score_gpt":0.270869354633609,"score_spread":0.2478187521958156,"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."}}