Research Article
Moving Object Classification Using 3D Point Cloud in Urban Traffic Environment
Table 4
Performance comparison of moving object classification algorithms.
| Object | Features | Classifier | AUC | Run time per object (ms) |
| Vehicle | 18 | SVM | 0.950 | 40.67 | SVM-BDT | 0.989 | 77.89 | 68 | SVM | 0.980 | 60.45 | SVM-BDT | 0.991 | 88.38 |
| Pedestrian | 18 | SVM | 0.953 | 39.77 | SVM-BDT | 0.976 | 72.38 | 68 | SVM | 0.969 | 57.42 | SVM-BDT | 0.985 | 83.93 |
| Bicycle | 18 | SVM | 0.859 | 42.94 | SVM-BDT | 0.958 | 75.83 | 68 | SVM | 0.902 | 59.94 | SVM-BDT | 0.968 | 85.01 |
| Crowd | 18 | SVM | 0.845 | 41.70 | SVM-BDT | 0.931 | 75.33 | 68 | SVM | 0.923 | 58.87 | SVM-BDT | 0.933 | 84.15 |
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