Research Article
Data Association Methods via Video Signal Processing in Imperfect Tracking Scenarios: A Review and Evaluation
Table 3
Classification of video MOT datasets.
| Name | Number of goals | Number of boxes | Camera mode | Scale | Tracking category | Features | Scenes |
| TownCenter [66] | 16 | — | Stable | 4500 | Pedestrian | Simple; annotation is complete; clear; blocked frequently | 1 | PETS09-S2L1 [67] | 8 | — | Stable | 795 | Pedestrian | Sparse crowd; high-speed nonlinear mode; blocked frequently | 1 | TUD-Stadtmitte [68] | — | — | Stable | 179 | Pedestrian | Low angle of view; severe mutual occlusion; complete occlusion | 1 | Parking Lot [69] | 14 | — | Stable | 1000 | Pedestrian | Parking lot; mutual blocking is more serious than TUD | 2 | PETS09-S2L2 [39] | — | — | Stable | 168 | Pedestrian | Medium-density crowds; high speed; blocked severely | 1 | MOT16 [56] | 517 | 110407 | Mobile/stable | 5316 | Pedestrian | Many scenes; comprehensive data; large amount of data | 7 | MOT17 [70] | 1638 | 564228 | Mobile/stable | 15948 | Pedestrian | Many scenes; more comprehensive than MOT16, magnitude of the data is larger | 7 | MOT20 [70] | 2332 | 1336920 | Stable | 8931 | Pedestrian | Wide scene at night; high crowd density | 3 | UA-DETRAC [71] | 8250 | 1210000 | Stable | 140000 | Vehicle | Canon EOS 550D camera records at 25 fps; rich scenes; large data volume | 24 | KITTI [72] | — | 330000 | Mobile | 180 GB | Pedestrian/vehicle | Vehicle-mounted camera; up to 15 vehicles and 30 pedestrians in each image; various degrees of occlusion and truncation | >3 | MOTs [73] | 977 | 65213 | Mobile | 10870 | Pedestrian/vehicle | Pixel-level relabeling on the KITTI_Tracking and MOTS challenge | >10 | DukeMTMC [56] | 1404 | 65213 | Stable | 36411 | Pedestrian | Large HD video dataset, typical MOT scenario | 8 |
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