{"id":"W2914133668","doi":"10.3166/ria.32.s1.115-124","title":"An augmented reality registration algorithm based on the combination of KAZE and optical flow","year":2018,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Optical flow; Augmented reality; Computer science; Image registration; Computer vision; Flow (mathematics); Artificial intelligence; Algorithm; Mathematics; Image (mathematics); Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001217862,0.001104601,0.001971063,0.002929637,0.001019504,0.002379184,0.001437627,0.001482435,0.002599513],"category_scores_gemma":[0.001939493,0.001019809,0.001726248,0.002665399,0.0006961039,0.002911263,0.00256946,0.002047359,0.001904418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004266241,"about_ca_system_score_gemma":0.002075271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002072218,"about_ca_topic_score_gemma":0.002928864,"domain_scores_codex":[0.9984723,0.0002468356,0.00008856693,0.0003714415,0.0007022268,0.000118633],"domain_scores_gemma":[0.9993501,0.00009480768,0.0000773822,0.0001412136,0.0002863864,0.00004996571],"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":[0.0004184869,0.0002065206,0.001188786,0.0002786076,0.0002238468,0.0001729193,0.0002081176,0.03014549,0.06569998,0.01659473,0.007700372,0.8771622],"study_design_scores_gemma":[0.0000941969,0.0003113618,0.002126467,0.00005515656,0.000217194,0.001389165,0.0001041038,0.8973593,0.06003913,0.008796134,0.02929016,0.0002176464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003870102,0.0001922262,0.9939232,0.00009399305,0.0001270483,0.00005359967,0.00005822768,0.0009191458,0.0007624445],"genre_scores_gemma":[0.05574937,0.0003847756,0.9405112,0.00009970316,0.00008255803,0.0001096038,0.0003147856,0.0002060335,0.002542056],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002929637,"threshold_uncertainty_score":0.008696198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0441519084004467,"score_gpt":0.3171379022723084,"score_spread":0.2729859938718617,"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."}}