{"id":"W2911261841","doi":"10.1109/crv.2019.00031","title":"Commodifying Pointing in HRI: Simple and Fast Pointing Gesture Detection from RGB-D Images","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"RGB color model; Computer vision; Artificial intelligence; Computer science; Gesture; Pixel; Ground plane; Point (geometry); Frame rate; Robot; Frame (networking); Ground truth; Detector; Exploit; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003984996,0.0007466268,0.0006245828,0.0004952602,0.000213431,0.0006970754,0.001068536,0.0007571371,0.009711686],"category_scores_gemma":[0.001041256,0.0003577946,0.0002832958,0.0004537161,0.0003544708,0.0005280106,0.0008769985,0.0005160809,0.006181124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002323817,"about_ca_system_score_gemma":0.0003116653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001604415,"about_ca_topic_score_gemma":0.003682385,"domain_scores_codex":[0.9994841,0.00004185489,0.00002044195,0.0001295211,0.0002574282,0.00006650991],"domain_scores_gemma":[0.9995649,0.00008450808,0.0000576256,0.0001633897,0.00009081452,0.00003864117],"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":[0.0003744812,0.00009555413,0.002195937,0.0004121792,0.00004774147,0.0003109305,0.000193207,0.007714514,0.3811554,0.001463969,0.01018528,0.5958507],"study_design_scores_gemma":[0.00008253445,0.0005470357,0.03747094,0.0001768545,0.0000609671,0.001791781,0.0001803987,0.3063464,0.6023362,0.003641717,0.04717752,0.0001877915],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07009298,0.000692491,0.8898604,0.0001990401,0.0001860307,0.0002621848,0.00136971,0.02459908,0.01273811],"genre_scores_gemma":[0.3781277,0.0004656339,0.6062495,0.0002293269,0.00006226934,0.0002066891,0.001065366,0.0009352965,0.01265836],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009711686,"threshold_uncertainty_score":0.03248882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01880108468758575,"score_gpt":0.2483414521576698,"score_spread":0.2295403674700841,"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."}}