{"id":"W2093909263","doi":"10.1109/sitis.2013.43","title":"Motion Estimation in Blurred Frames Using Phase Correlation","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Motion estimation; Phase correlation; Motion vector; Computer vision; Artificial intelligence; Computer science; Quarter-pixel motion; Motion blur; Correlation; Motion (physics); Noise (video); Phase (matter); Mathematics; Image (mathematics); Physics; Fourier transform","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":[0.0006020657,0.0008246593,0.0008321208,0.00143704,0.0004494829,0.0005694716,0.0006498676,0.0007015704,0.00189716],"category_scores_gemma":[0.002630783,0.0004584907,0.0005878037,0.001248857,0.0002971205,0.00131512,0.0006660948,0.0007456302,0.0007947887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003186338,"about_ca_system_score_gemma":0.0006953514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002428312,"about_ca_topic_score_gemma":0.00306424,"domain_scores_codex":[0.9995963,0.00007135586,0.00002900644,0.00007960929,0.0001915707,0.0000321726],"domain_scores_gemma":[0.9993055,0.0002316587,0.0001132834,0.000109167,0.0002130756,0.00002732709],"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":[0.0002974677,0.00009269557,0.001435146,0.0003017311,0.0001051137,0.0002102846,0.0002120896,0.04549525,0.2326766,0.008039208,0.001665329,0.709469],"study_design_scores_gemma":[0.0000746302,0.0003320533,0.003786645,0.00008276992,0.0001421759,0.001084971,0.00007301271,0.7686189,0.1998071,0.004499138,0.02139153,0.0001070814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00914524,0.0003003431,0.989576,0.00003226739,0.00003933881,0.00003427908,0.0000301394,0.0003223179,0.0005202315],"genre_scores_gemma":[0.08235157,0.0007009613,0.9148929,0.0000536251,0.00007099118,0.0000487764,0.0001728078,0.0001100754,0.001598397],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002428312,"threshold_uncertainty_score":0.006346643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221713513074497,"score_gpt":0.3279127560648183,"score_spread":0.3056956209340733,"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."}}