{"id":"W1973882119","doi":"10.1016/j.imavis.2008.10.008","title":"Photo Hull regularized stereo","year":2008,"lang":"en","type":"article","venue":"Image and Vision Computing","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visual hull; Regularization (linguistics); Hull; Computer vision; Computer science; Artificial intelligence; 3D reconstruction; Carving; Algorithm; Iterative reconstruction; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004030133,0.0007104828,0.001132001,0.001195543,0.0003448312,0.001189538,0.001136151,0.001144156,0.008947048],"category_scores_gemma":[0.001502255,0.0007470524,0.0007847037,0.001274121,0.0005425639,0.00123521,0.001748129,0.001353026,0.002860891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006184531,"about_ca_system_score_gemma":0.001350046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006195086,"about_ca_topic_score_gemma":0.008078715,"domain_scores_codex":[0.9992642,0.00008682236,0.00002272573,0.0001681656,0.0003773457,0.00008071461],"domain_scores_gemma":[0.999391,0.00008128446,0.00005317685,0.000266354,0.0001711816,0.00003700523],"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":[0.0004530294,0.0001609032,0.0007471804,0.0002039904,0.0001175215,0.0001041025,0.00007158079,0.293661,0.0408161,0.02454554,0.02037511,0.618744],"study_design_scores_gemma":[0.00001628253,0.00002569568,0.0003849906,0.00001047308,0.00001026566,0.00008638299,0.00001257971,0.9815446,0.006719263,0.006680911,0.004494899,0.00001361178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008271354,0.0001399969,0.9854139,0.0001291165,0.00006639976,0.0000413283,0.0003850611,0.001390104,0.004162779],"genre_scores_gemma":[0.3201305,0.0003802877,0.6589978,0.0003065495,0.0001122092,0.0001112579,0.002416409,0.0008268998,0.01671816],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008947048,"threshold_uncertainty_score":0.02993083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0162120314473088,"score_gpt":0.3105531909714388,"score_spread":0.29434115952413,"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."}}