{"id":"W2170198060","doi":"10.1109/ccece.2004.1349631","title":"Estimation of epipolar geometry from homography using global optical flow","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Epipolar geometry; Fundamental matrix (linear differential equation); Homography; Optical flow; Computer vision; Artificial intelligence; Computer science; Frame (networking); Motion estimation; Flow (mathematics); Rank (graph theory); Singular value decomposition; Essential matrix; Motion (physics); Mathematics; Image (mathematics); Geometry; Projective test; Symmetric matrix; Mathematical analysis; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005713589,0.001360443,0.001260716,0.002759419,0.0004887131,0.0009666765,0.0006891339,0.0007311326,0.002501152],"category_scores_gemma":[0.002200036,0.000685708,0.0008887788,0.001294584,0.0005288404,0.001967304,0.0009885014,0.00115277,0.0008778186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004663286,"about_ca_system_score_gemma":0.0009659008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003464874,"about_ca_topic_score_gemma":0.004850524,"domain_scores_codex":[0.9994088,0.000102859,0.00002133322,0.0001631064,0.0002433024,0.00006059159],"domain_scores_gemma":[0.9994643,0.0001364202,0.00008317755,0.0001101061,0.0001645192,0.00004149502],"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":[0.0002081562,0.0001105419,0.001567636,0.0002808355,0.0002110098,0.0002219906,0.000206661,0.118371,0.09953596,0.01420375,0.00346387,0.7616185],"study_design_scores_gemma":[0.00004592884,0.0002472097,0.005706713,0.00003499434,0.00007916562,0.0004957449,0.0001096359,0.9253759,0.04468598,0.01676671,0.006382444,0.00006958043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02015124,0.0002173134,0.9778976,0.00004013803,0.00003026131,0.00004985236,0.0000939489,0.0006083661,0.0009112038],"genre_scores_gemma":[0.2437233,0.0008177821,0.7523342,0.00003705165,0.00008487357,0.00008068157,0.000709473,0.000245774,0.001966752],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003464874,"threshold_uncertainty_score":0.00836724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01245276564107062,"score_gpt":0.2848162837862152,"score_spread":0.2723635181451446,"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."}}