{"id":"W4237211705","doi":"10.32920/ryerson.14661516","title":"Autonomous stereo vision system for depth computation of moving object","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer vision; Artificial intelligence; Background subtraction; Computer science; Stereopsis; Computer stereo vision; Computation; Stereoscopy; Kalman filter; Thresholding; Depth map; Filter (signal processing); Pixel; Image (mathematics); Algorithm","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":[0.0002412986,0.0002883402,0.0003797468,0.0006913372,0.0003697348,0.0004389512,0.0009139386,0.000632623,0.007169696],"category_scores_gemma":[0.0003232411,0.0002145182,0.0002815934,0.0005983005,0.0001196574,0.0004179173,0.0004576773,0.0004065027,0.00307331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005147171,"about_ca_system_score_gemma":0.0009592737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003120271,"about_ca_topic_score_gemma":0.002933108,"domain_scores_codex":[0.9996482,0.00002996191,0.00001210109,0.00006917574,0.000207942,0.00003255009],"domain_scores_gemma":[0.9998267,0.00001122568,0.00001289041,0.00003196744,0.0001032195,0.00001400376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003304732,0.0001463267,0.001682577,0.0002711964,0.00006230119,0.0001847845,0.000218569,0.007488686,0.3889507,0.01291957,0.02244939,0.5652954],"study_design_scores_gemma":[0.0003519807,0.0007195356,0.0138781,0.00006583066,0.0001535441,0.001684941,0.0001132094,0.4656653,0.3185793,0.008105565,0.1905466,0.0001362802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03065228,0.0005525782,0.9412749,0.0001144323,0.0001868036,0.0002408298,0.000820542,0.01153613,0.01462154],"genre_scores_gemma":[0.4246033,0.0003603712,0.5554836,0.0002513448,0.0001227037,0.0004131987,0.001820639,0.0002525671,0.01669234],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007169696,"threshold_uncertainty_score":0.02398503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02409835943381176,"score_gpt":0.3187938593059672,"score_spread":0.2946954998721554,"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."}}