{"id":"W2060453172","doi":"10.1109/ismar.2013.6671788","title":"Third person perspective augmented reality for high accuracy applications","year":2013,"lang":"en","type":"article","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Bentley (Canada)","funders":"","keywords":"Perspective (graphical); Mobile device; Computer science; Augmented reality; Orientation (vector space); Computer vision; Artificial intelligence; Degrees of freedom (physics and chemistry); Computer graphics (images); 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":[0.0004871538,0.001037658,0.0005842207,0.0005057551,0.0003270101,0.001151847,0.0009255462,0.001086842,0.005928348],"category_scores_gemma":[0.001320413,0.0004147785,0.0009357263,0.0005443043,0.0003560056,0.001197723,0.001318353,0.001090671,0.002064555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002160588,"about_ca_system_score_gemma":0.0002922369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009833173,"about_ca_topic_score_gemma":0.001223455,"domain_scores_codex":[0.9990958,0.0002019399,0.00003163237,0.0001149292,0.000477941,0.00007774022],"domain_scores_gemma":[0.9992199,0.0001992843,0.00006212508,0.0002671211,0.000203504,0.00004805995],"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":[0.0006432198,0.0001043387,0.001572299,0.0006338207,0.0001721067,0.001017863,0.0006471765,0.03663993,0.312566,0.01941874,0.009971118,0.6166134],"study_design_scores_gemma":[0.0001241215,0.001428571,0.005509335,0.0002386878,0.0003054421,0.007186593,0.0002771035,0.4756103,0.3054863,0.01469743,0.1888056,0.0003305327],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01362567,0.001469101,0.977848,0.0001896587,0.000231526,0.00003984387,0.000119641,0.001992,0.00448464],"genre_scores_gemma":[0.4194393,0.00260376,0.5690727,0.0002740138,0.0002534747,0.00009172352,0.0004309602,0.0002748435,0.007559225],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005928348,"threshold_uncertainty_score":0.01983225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03451416831702474,"score_gpt":0.3056636820317115,"score_spread":0.2711495137146868,"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."}}