{"id":"W1543134425","doi":"10.1002/9781118583593.ch3","title":"2D‐to‐3D Video Conversion: Overview and Perspectives","year":2013,"lang":"en","type":"other","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Computer science; Stereoscopy; Video processing; 2D to 3D conversion; Video post-processing; Multiview Video Coding; Computer vision; Visualization; Artificial intelligence; Pace; Video tracking; Computer graphics (images); Multimedia; Image (mathematics); Geography","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":[0.0004912173,0.0006544901,0.0003892013,0.002843578,0.0004251616,0.00296281,0.0008975211,0.001335429,0.01549823],"category_scores_gemma":[0.0006336467,0.0005288586,0.0005166178,0.002753957,0.0006545135,0.002839718,0.000959028,0.0015945,0.005780913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008493003,"about_ca_system_score_gemma":0.0006163706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001679106,"about_ca_topic_score_gemma":0.00141484,"domain_scores_codex":[0.9995872,0.00004417855,0.00002197196,0.00005938816,0.0002532922,0.0000339453],"domain_scores_gemma":[0.9996749,0.0001263977,0.0000175711,0.00002085647,0.0001387209,0.00002157812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005348858,0.00008117677,0.0003851479,0.002183421,0.0000198545,0.0002570137,0.0002328269,0.003481538,0.007401203,0.07320995,0.02444226,0.8882521],"study_design_scores_gemma":[0.000007091773,0.00009694567,0.0009876258,0.00124367,0.00001660875,0.002029308,0.0003458519,0.009480859,0.007989564,0.0194471,0.9583012,0.00005421583],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004338831,0.5994902,0.1877188,0.00251692,0.002161616,0.0001592626,0.0003616415,0.0009319366,0.2023208],"genre_scores_gemma":[0.05128554,0.733224,0.1316362,0.001224907,0.002985178,0.0001827417,0.001026712,0.0003408818,0.0780938],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01549823,"threshold_uncertainty_score":0.05184674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02429493128790938,"score_gpt":0.2863121475552594,"score_spread":0.26201721626735,"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."}}