{"id":"W2117157485","doi":"10.1109/icme.2009.5202424","title":"Rate-distortion analysis of rectification-based view interpolation for multiview video coding","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Rectification; Interpolation (computer graphics); Computer science; Coding (social sciences); Computer vision; Artificial intelligence; Distortion (music); Compensation (psychology); Image scaling; Mathematics; Image processing; Image (mathematics); Telecommunications; Engineering; Statistics","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":[0.001419204,0.0006838005,0.0005074433,0.0008000367,0.0001890439,0.0005407023,0.0006852069,0.0004698159,0.001908851],"category_scores_gemma":[0.005102577,0.0002470283,0.0004502767,0.0006752367,0.0003984567,0.0009055716,0.0005768588,0.0006307085,0.0003853482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00083419,"about_ca_system_score_gemma":0.0004445272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001601413,"about_ca_topic_score_gemma":0.000836105,"domain_scores_codex":[0.9989985,0.000193358,0.00004205071,0.00007148621,0.0006323251,0.00006234549],"domain_scores_gemma":[0.9979141,0.001058842,0.0002069472,0.0002182494,0.0005740863,0.00002768618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007271171,0.00009273779,0.002136816,0.0004078125,0.0001108069,0.0004361259,0.0002593052,0.5725531,0.111832,0.07230153,0.00195804,0.2371847],"study_design_scores_gemma":[0.000005342933,0.00006903461,0.0004122457,0.00001339616,0.00001149772,0.0002745904,0.00001504949,0.9779513,0.01772453,0.002803713,0.0007033352,0.00001593848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03880022,0.001773429,0.9563233,0.0001246994,0.0000348771,0.00004668719,0.00007112676,0.0001541538,0.002671383],"genre_scores_gemma":[0.75242,0.002563943,0.2420463,0.00005773747,0.00008712372,0.00009319258,0.000261992,0.00009440682,0.002375276],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001908851,"threshold_uncertainty_score":0.007505536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03117714362178951,"score_gpt":0.3363855756988531,"score_spread":0.3052084320770636,"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."}}