{"id":"W2152705230","doi":"10.1109/cvpr.2013.335","title":"Sampling Strategies for Real-Time Action Recognition","year":2013,"lang":"en","type":"article","venue":"","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Histogram; Pattern recognition (psychology); Kernel (algebra); Artificial intelligence; Sampling (signal processing); Feature (linguistics); Action recognition; Grid; Histogram of oriented gradients; Intersection (aeronautics); Action (physics); Feature extraction; Data mining; Detector; Mathematics; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009020126,0.0000724209,0.00006779537,0.0000793415,0.0001397663,0.0004229129,0.00011804,0.00004656619,0.0006646654],"category_scores_gemma":[0.000009661699,0.00006618416,0.00004693182,0.00009358673,0.00000899533,0.002074685,0.00001862283,0.00004043381,0.001942995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002112007,"about_ca_system_score_gemma":0.00002944957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000784166,"about_ca_topic_score_gemma":0.000008634163,"domain_scores_codex":[0.9994392,0.00001710293,0.0001169259,0.0001956797,0.00008180382,0.0001493339],"domain_scores_gemma":[0.9995403,0.00007699077,0.00005465608,0.0001288215,0.0001558131,0.00004343707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000005812044,0.00006608796,0.000005525916,0.00003272097,0.00001978712,2.837673e-7,0.0002253071,0.00001875633,0.1115347,0.01856989,0.01887357,0.8506475],"study_design_scores_gemma":[0.0009352791,0.0003480624,0.001889776,0.00005818171,0.00002042488,0.00002483859,0.0009377368,0.1074884,0.05434433,0.8212347,0.01205265,0.0006655974],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1234194,0.000001825935,0.8500925,0.0005865297,0.0002118504,0.00033201,0.000002021796,0.00043592,0.02491802],"genre_scores_gemma":[0.6421222,0.0000646965,0.3499624,0.0007951526,0.000575928,0.00050607,0.0001316043,0.0000239791,0.005817997],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8499819,"threshold_uncertainty_score":0.9988341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08993953883839159,"score_gpt":0.3079407743370325,"score_spread":0.2180012354986409,"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."}}