{"id":"W2168735438","doi":"10.1109/crv.2006.53","title":"Object Extraction and Reconstruction in Active Video","year":2006,"lang":"en","type":"article","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science; Object (grammar); Gestalt psychology; Video tracking; 3D single-object recognition; Cognitive neuroscience of visual object recognition; Motion (physics); Block-matching algorithm; Method; Object-oriented programming; Psychology","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":[0.0007222731,0.0006093433,0.0007778914,0.001373449,0.0003043227,0.001047276,0.001118661,0.001050883,0.001109016],"category_scores_gemma":[0.001874771,0.0005778932,0.000727998,0.001092767,0.0008773123,0.001878858,0.001093284,0.0007716663,0.0006779456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003878845,"about_ca_system_score_gemma":0.0003317334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009291003,"about_ca_topic_score_gemma":0.0007828794,"domain_scores_codex":[0.9994196,0.0001051005,0.00003281497,0.00016381,0.0002236735,0.00005516176],"domain_scores_gemma":[0.9993652,0.0002671156,0.00009333602,0.00011735,0.0001302922,0.00002683917],"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":[0.0002618286,0.00007575752,0.00101194,0.0003106615,0.00007959675,0.0003711513,0.0005005526,0.1082387,0.1325469,0.06735568,0.002198849,0.6870484],"study_design_scores_gemma":[0.00002344443,0.0001031473,0.0009429682,0.00003115238,0.00002666704,0.0004519473,0.00008631343,0.8901511,0.06842465,0.02981332,0.009905807,0.00003942896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002644869,0.0001050866,0.9967765,0.00002431264,0.00001049951,0.00001425595,0.00001351466,0.000127347,0.0002835195],"genre_scores_gemma":[0.1098913,0.0005086045,0.8866174,0.00007805602,0.00006747582,0.00009425092,0.0002083899,0.0000895768,0.002444916],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001373449,"threshold_uncertainty_score":0.003819823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005615951392029579,"score_gpt":0.2176837005024294,"score_spread":0.2120677491103998,"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."}}