{"id":"W1978479866","doi":"10.1109/tip.2013.2282897","title":"Saliency-Aware Video Compression","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":328,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Computer vision; Region of interest; Artificial intelligence; Coding (social sciences); Multiview Video Coding; Data compression; Salient; Video tracking; Video processing; Mathematics","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":[0.0002023072,0.0004490769,0.000358328,0.0009018772,0.0001847367,0.0002864026,0.0005035228,0.0002905636,0.0012151],"category_scores_gemma":[0.001140945,0.0001317092,0.0003200886,0.0004946488,0.0002396003,0.0006164493,0.0004285872,0.0003108178,0.0002534382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002714964,"about_ca_system_score_gemma":0.0002333725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009415608,"about_ca_topic_score_gemma":0.00108201,"domain_scores_codex":[0.9997999,0.00002421293,0.000007866816,0.00003333411,0.0001178161,0.00001676902],"domain_scores_gemma":[0.9996924,0.00009478318,0.00003565978,0.00003926315,0.0001219979,0.00001582034],"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":[0.0003713467,0.00008812263,0.0006113558,0.0003008994,0.00005003381,0.0003138568,0.000162185,0.0227694,0.4129642,0.005851558,0.002712193,0.5538048],"study_design_scores_gemma":[0.00005527505,0.0004194,0.004282481,0.00004781139,0.00007251854,0.001783271,0.00006900248,0.6882557,0.2905695,0.004876441,0.009511837,0.00005673619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06268413,0.00200902,0.9301605,0.0001467647,0.0001117699,0.0001195927,0.00009608663,0.001015252,0.003656839],"genre_scores_gemma":[0.6592674,0.001284237,0.3353306,0.0001427425,0.0001591734,0.0000744483,0.0002205874,0.0001298547,0.00339106],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0012151,"threshold_uncertainty_score":0.004064918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01602340534697727,"score_gpt":0.271601545481045,"score_spread":0.2555781401340678,"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."}}