{"id":"W1524559442","doi":"10.1007/978-3-642-12304-7_8","title":"Two-View Geometry and Reconstruction under Quasi-perspective Projection","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Homography; Perspective (graphical); Computer science; Fundamental matrix (linear differential equation); Invariant (physics); Projective geometry; Parallel projection; Degrees of freedom (physics and chemistry); Projection (relational algebra); Pencil (optics); Cross-ratio; Projective test; Computer vision; Geometry; Algebra over a field; Orthographic projection; Mathematics; Artificial intelligence; Algorithm; Pure mathematics; Projective space; Mathematical analysis; Algebraic geometry; Physics; Optics","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":[0.0005078105,0.001015706,0.0008816657,0.00124203,0.0003712268,0.002620487,0.001050198,0.001224179,0.004473452],"category_scores_gemma":[0.001653138,0.001146523,0.001057114,0.001315124,0.001471078,0.003722633,0.002300978,0.002721574,0.001647773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003623012,"about_ca_system_score_gemma":0.0003051577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008443096,"about_ca_topic_score_gemma":0.0005011231,"domain_scores_codex":[0.999306,0.0001265678,0.00003477698,0.0001551518,0.0003293678,0.00004810674],"domain_scores_gemma":[0.999294,0.0002474217,0.000104183,0.0001917961,0.0001173278,0.00004509865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002303755,0.00004085392,0.0004322425,0.0003937959,0.00007141574,0.000580968,0.0004093392,0.03053395,0.03721157,0.7595007,0.006652947,0.1639418],"study_design_scores_gemma":[0.00005000774,0.0001277238,0.001595135,0.00005208052,0.00004603881,0.004733658,0.0002517435,0.3339322,0.02372124,0.6139115,0.02147291,0.0001057569],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00910297,0.0005940903,0.9824921,0.000233447,0.00009046117,0.00002092179,0.0001669884,0.0002027136,0.007096297],"genre_scores_gemma":[0.3100416,0.0036425,0.6615891,0.0001852956,0.000312414,0.00006769222,0.0009880164,0.0005197154,0.02265376],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004473452,"threshold_uncertainty_score":0.01496518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01587892090698607,"score_gpt":0.2861686202840409,"score_spread":0.2702896993770549,"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."}}