{"id":"W2006385691","doi":"10.1109/3dpvt.2006.136","title":"The Reverse Projection Correlation Principle for Depth from Defocus","year":2006,"lang":"en","type":"article","venue":"","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Pixel; Radiance; Focus (optics); Computer vision; Artificial intelligence; Projection (relational algebra); Computer science; Position (finance); Invariant (physics); Correlation; Mathematics; Optics; Algorithm; Geometry; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004849606,0.00004398068,0.00002931482,0.00001132618,0.0001449449,0.00004101817,0.00004833156,0.00003105835,0.000004324059],"category_scores_gemma":[0.000007069395,0.00003198126,0.00001963909,0.00006162732,0.000009304152,0.00006164012,0.000005727459,0.00003793094,0.000009474292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003112273,"about_ca_system_score_gemma":0.000005944519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001185381,"about_ca_topic_score_gemma":0.0001925899,"domain_scores_codex":[0.9997351,0.000002209068,0.00008797836,0.00006271925,0.00003494542,0.00007710462],"domain_scores_gemma":[0.9998171,0.0000339662,0.00001552351,0.00009833114,0.00002797995,0.000007100652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004982237,0.0001382494,0.006905679,0.0001140256,0.00005679213,8.91972e-7,0.0002075582,0.03552469,0.04806316,0.1551554,0.3811597,0.372624],"study_design_scores_gemma":[0.000151413,0.000009808387,0.002319902,0.000008566634,0.00001450112,0.000001497213,0.00001896605,0.6236411,0.03994779,0.0277309,0.3060353,0.000120285],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007020241,0.00009069769,0.9802927,0.0001131241,0.00006710395,0.0003015201,0.000004707116,0.0006254556,0.01148443],"genre_scores_gemma":[0.8743823,0.00001668987,0.1225025,0.00001877797,0.0001562119,0.0003924906,0.00005070673,0.0000213854,0.002458987],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.867362,"threshold_uncertainty_score":0.1304158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009925721310999917,"score_gpt":0.2458262722155967,"score_spread":0.2359005509045968,"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."}}