{"id":"W2029577819","doi":"10.1117/12.389344","title":"<title>Image-based view synthesis for enhanced perception in teleoperation</title>","year":2000,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Augmented reality; Teleoperation; Computer vision; Computer science; Rendering (computer graphics); Artificial intelligence; Triangulation; Merge (version control); View synthesis; Affine transformation; Robot; 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":[0.0003162632,0.0003627223,0.0004855526,0.0004034225,0.0001729219,0.000897888,0.0006299288,0.0005219892,0.0322159],"category_scores_gemma":[0.0004828238,0.000169127,0.0002693713,0.0004993042,0.0004415584,0.001167401,0.0005238865,0.0005847569,0.006557093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003618028,"about_ca_system_score_gemma":0.0001813299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000971897,"about_ca_topic_score_gemma":0.001300684,"domain_scores_codex":[0.9997957,0.00004047942,0.000006461888,0.00003690642,0.0001006963,0.00001975754],"domain_scores_gemma":[0.9997372,0.00009946009,0.00001386515,0.00006200799,0.00006825375,0.00001917495],"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":[0.0007103504,0.0001495866,0.0004348543,0.0003479786,0.00003855383,0.0003016077,0.000139869,0.02847909,0.2145719,0.02332032,0.04511072,0.6863952],"study_design_scores_gemma":[0.0001353127,0.0005407482,0.002266874,0.00009233495,0.00003600291,0.0007451177,0.0001203162,0.579299,0.2263246,0.01251708,0.1778535,0.00006929485],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02480067,0.002099941,0.9214225,0.0006024143,0.0008501717,0.0001285543,0.00028132,0.004232946,0.0455815],"genre_scores_gemma":[0.3512746,0.002515319,0.5375156,0.000295101,0.0004106507,0.0001298953,0.001394497,0.001536875,0.1049275],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0322159,"threshold_uncertainty_score":0.1077729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009497232325894295,"score_gpt":0.2418389409243499,"score_spread":0.2323417085984556,"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."}}