{"id":"W2998060566","doi":"10.3390/s20010138","title":"Fast Method of Registration for 3D RGB Point Cloud with Improved Four Initial Point Pairs Algorithm","year":2019,"lang":"en","type":"article","venue":"Sensors","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Anhui Provincial Department of Education; Chuzhou University","keywords":"Point cloud; RGB color model; Iterative closest point; Computer science; Artificial intelligence; Computer vision; Point (geometry); Algorithm; Transformation (genetics); Similarity (geometry); Rigid transformation; Filter (signal processing); Mathematics; Image (mathematics); Geometry","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":[0.001411192,0.001836004,0.002058096,0.00414843,0.001447764,0.002136549,0.003337089,0.001414678,0.006291374],"category_scores_gemma":[0.003123656,0.001242237,0.002906412,0.004939237,0.0009693524,0.002562764,0.003568104,0.002528313,0.004556297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009386543,"about_ca_system_score_gemma":0.002869285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007180906,"about_ca_topic_score_gemma":0.004358054,"domain_scores_codex":[0.9959704,0.000474797,0.0002502427,0.0009332316,0.002111536,0.0002597674],"domain_scores_gemma":[0.9987061,0.0001546785,0.00009643586,0.0002913111,0.0007030333,0.00004848217],"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":[0.0002602873,0.00009933818,0.001805443,0.0003699223,0.0001939731,0.0002188386,0.0003221413,0.08657943,0.03949571,0.01619513,0.01240938,0.8420503],"study_design_scores_gemma":[0.00008683162,0.0001540027,0.002120869,0.00003266715,0.0000794305,0.000630545,0.000129436,0.9202334,0.04143742,0.008810189,0.02613285,0.0001522395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00125261,0.00006847267,0.9969921,0.0000256632,0.00004180237,0.00006132275,0.00005902932,0.001048438,0.0004505516],"genre_scores_gemma":[0.0331091,0.0002056374,0.9629148,0.00004023661,0.00004226753,0.0003396439,0.0008393583,0.0004763485,0.002032509],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007180906,"threshold_uncertainty_score":0.0210467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02079514166478992,"score_gpt":0.2450731104112503,"score_spread":0.2242779687464604,"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."}}