{"id":"W1979828718","doi":"10.1109/icip.2006.312674","title":"3D Reconstruction Based on a Hybrid Disparity Estimation Algorithm","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pixel; Artificial intelligence; Computer science; Matching (statistics); Scheme (mathematics); Algorithm; Computer vision; Image segmentation; Segmentation; Iterative reconstruction; Estimation; Image (mathematics); Hybrid algorithm (constraint satisfaction); Pattern recognition (psychology); Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00008791722,0.00007148436,0.00006300954,0.00007649888,0.00009733187,0.00009287067,0.0001151597,0.00001232179,0.00003816148],"category_scores_gemma":[0.00001712156,0.00006226781,0.00002623463,0.0001483994,0.00001915192,0.0005284244,0.00002737316,0.00006460208,0.00006875102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003704637,"about_ca_system_score_gemma":0.00001870554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004047224,"about_ca_topic_score_gemma":0.000001884566,"domain_scores_codex":[0.9993561,0.00002137631,0.0001225238,0.0002263182,0.0001495187,0.0001241794],"domain_scores_gemma":[0.9996049,0.00003781511,0.00004406986,0.0002465009,0.00003439853,0.00003225038],"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":[8.803677e-7,0.00002656257,0.00008110957,0.000001202478,3.269429e-7,0.000002626401,0.000001538096,0.004081807,0.00005748435,0.00214491,0.0004184221,0.9931831],"study_design_scores_gemma":[0.0001917975,0.00002107729,0.001501383,0.000012604,7.691172e-7,0.00002021375,9.425328e-7,0.9867051,0.004001366,0.006826404,0.0006337406,0.0000846406],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005335833,0.000003713368,0.9868152,0.0005829624,0.0002653668,0.00006109243,8.919134e-7,0.0002403658,0.01149681],"genre_scores_gemma":[0.1157148,5.121142e-7,0.8835822,0.0004567192,0.00003279734,0.00000365934,0.000004262867,0.000003102969,0.0002020288],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9930985,"threshold_uncertainty_score":0.2539208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006827322593351194,"score_gpt":0.2423537194687833,"score_spread":0.2355263968754321,"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."}}