MOTSynth-MOT-CVPR22 Results
Click on a measure to sort the table accordingly. See below for a more detailed description.
| Tracker | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag | Hz | |
| Tracktor++v2 1.   |
56.5 ±11.4 | 53.0 | 42.8 | 205 (26.1) | 205 (26.1) | 10,891 | 70,032 | 62.8 | 91.6 | 39.7 | 46.5 | 43.8 | 73.1 | 50.1 | 73.1 | 79.4 | 1.8 | 946 (0.0) | 1,594 (0.0) | 1.5 | |
| P. Bergmann, T. Meinhardt, L. Leal-Taixé. Tracking without bells and whistles. In ICCV, 2019. | |||||||||||||||||||||
| Sequences | Frames | Trajectories | Boxes |
| 7 | 5919 | 785 | 188076 |
Difficulty Analysis
Sequence difficulty (from easiest to hardest, measured by average MOTA)
MOT17-03
(66.1 MOTA)
MOT17-07
(59.2 MOTA)
MOT17-06
(55.7 MOTA)
...
...
MOT17-08
(34.9 MOTA)
MOT17-14
(33.5 MOTA)
Evaluation Measures
Lower is better. Higher is better.| Measure | Better | Perfect | Description |
| MOTA | higher | 100% | Multi-Object Tracking Accuracy (+/- denotes standard deviation across all sequences) [1]. This measure combines three error sources: false positives, missed targets and identity switches. |
| IDF1 | higher | 100% | ID F1 Score [2]. The ratio of correctly identified detections over the average number of ground-truth and computed detections. |
| HOTA | higher | 100% | Higher Order Tracking Accuracy [3]. Geometric mean of detection accuracy and association accuracy. Averaged across localization thresholds. |
| MT | higher | 100% | Mostly tracked targets. The ratio of ground-truth trajectories that are covered by a track hypothesis for at least 80% of their respective life span. |
| ML | lower | 0% | Mostly lost targets. The ratio of ground-truth trajectories that are covered by a track hypothesis for at most 20% of their respective life span. |
| FP | lower | 0 | The total number of false positives. |
| FN | lower | 0 | The total number of false negatives (missed targets). |
| Rcll | higher | 100% | Ratio of correct detections to total number of GT boxes. |
| Prcn | higher | 100% | Ratio of TP / (TP+FP). |
| AssA | higher | 100% | Association Accuracy [3]. Association Jaccard index averaged over all matching detections and then averaged over localization thresholds. |
| DetA | higher | 100% | Detection Accuracy [3]. Detection Jaccard index averaged over localization thresholds. |
| AssRe | higher | 100% | Association Recall [3]. TPA / (TPA + FNA) averaged over all matching detections and then averaged over localization thresholds. |
| AssPr | higher | 100% | Association Precision [3]. TPA / (TPA + FPA) averaged over all matching detections and then averaged over localization thresholds. |
| DetRe | higher | 100% | Detection Recall [3]. TP /(TP + FN) averaged over localization thresholds. |
| DetPr | higher | 100% | Detection Precision [3]. TP /(TP + FP) averaged over localization thresholds. |
| LocA | higher | 100% | Localization Accuracy [3]. Average localization similarity averaged over all matching detections and averaged over localization thresholds. |
| FAF | lower | 0 | The average number of false alarms per frame. |
| ID Sw. | lower | 0 | Number of Identity Switches (ID switch ratio = #ID switches / recall) [4]. Please note that we follow the stricter definition of identity switches as described in the reference |
| Frag | lower | 0 | The total number of times a trajectory is fragmented (i.e. interrupted during tracking). |
| Hz | higher | Inf. | Processing speed (in frames per second excluding the detector) on the benchmark. The frequency is provided by the authors and not officially evaluated by the MOTChallenge. |
Legend
| Symbol | Description |
|
This is an online (causal) method, i.e. the solution is immediately available with each incoming frame and cannot be changed at any later time. |
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This method used the provided detection set as input. |
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This method used a private detection set as input. |
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This entry has been submitted or updated less than a week ago. |
References:
| [1] | Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics. Image and Video Processing, 2008(1):1-10, 2008. |
| [2] | Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking. In ECCV workshop on Benchmarking Multi-Target Tracking, 2016. |
| [3] | HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking. International Journal of Computer Vision, 2020. |
| [4] | Learning to associate: HybridBoosted multi-target tracker for crowded scene. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2009. |
