{"id":"W4286580841","doi":"10.1109/lra.2022.3193246","title":"Reliable, Robust, Accurate and Real-Time 2D LiDAR Human Tracking in Cluttered Environment: A Social Dynamic Filtering Approach","year":2022,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Lidar; Computer vision; Artificial intelligence; Robustness (evolution); Video tracking; Tracking (education); Usability; Object (grammar); Human–computer interaction; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007117638,0.0001570765,0.0002186555,0.0001717825,0.0005024648,0.0002392009,0.0002475787,0.00004150771,0.000006605026],"category_scores_gemma":[0.000005189428,0.0001786256,0.00003651518,0.0002138508,0.00004391781,0.0003925729,0.0001770509,0.0002049899,0.000001759101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009231211,"about_ca_system_score_gemma":0.00001088842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003535184,"about_ca_topic_score_gemma":0.000002273795,"domain_scores_codex":[0.9985573,0.0002157779,0.0003042293,0.0004120985,0.0002332434,0.0002772928],"domain_scores_gemma":[0.9995303,0.00006162503,0.0001608908,0.0001988058,0.000007167241,0.00004125806],"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":[0.000007245782,0.00008822876,0.001716356,0.00008977845,0.00003023076,0.00004611926,0.003481721,0.8803815,0.100743,0.0007733298,0.0002241159,0.01241844],"study_design_scores_gemma":[0.0005517518,0.00003618272,0.05796642,0.0000176018,0.000008027337,0.00003028852,0.00004448853,0.9405425,0.0001180775,0.0003216873,0.00008216045,0.0002807933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4736592,0.00002651357,0.5237846,0.002046383,0.000120245,0.0001656441,0.000005349851,0.000120325,0.00007172878],"genre_scores_gemma":[0.8918441,0.00002481208,0.107497,0.0005043406,0.00003950149,0.00002649649,0.00001878574,0.00001830965,0.00002665794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4181848,"threshold_uncertainty_score":0.728414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0260939825446983,"score_gpt":0.2631230884860992,"score_spread":0.2370291059414009,"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."}}