DukeMTMCT Results

Click on a measure to sort the table accordingly. See below for a more detailed description.


Easy Test Set

Single Camera (all)

Tracker IDF1 IDP IDR MOTA MOTP FAF MT ML FP FN ID Sw. Frag
mtmct_hxq
1. online method
16.419.414.268.474.10.0381726425,155308,6629184,392
Anonymous submission
MTMC___DS
2. using public detections
70.884.361.065.275.80.0560311936,956330,3828554,669
Anonymous submission
MOT_TBA
3. online method
82.085.079.278.080.00.111,0184079,402152,3368031,466
Paper ID 648
d_b_v13
4.
89.091.187.088.478.60.051,112837,50984,8387241,954
Anonymous submission
MTMC_CDSC
5. using public detections
77.087.668.670.975.80.0574011038,655268,3986934,717
Y. Tesfaye, E. Zemene, A. Prati, M. Pelillo, M. Shah. Multi-Target Tracking in Multiple Non-Overlapping Cameras using Constrained Dominant Sets. In CoRR, 2017.
MTMC_ReIDp
6. using public detections
79.289.970.768.877.90.0772614352,408277,7624491,060
Z. Zhang, J. Wu, X. Zhang, C. Zhang. Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project. In , 2017.
SAS
7. using public detections
76.583.970.369.374.80.108138976,059248,2244262,081
Submission id 177
MYTRACKER
8. online method using public detections
80.387.374.478.378.40.059147235,580193,2534061,116
K. Yoon, Y. Song, M. Jeon. Multiple hypothesis tracking algorithm for multi-target multi-camera tracking with disjoint views. In IET Image Processing, 2018.
TAREIDMTMC
9. online method
83.887.680.483.375.50.061,0511744,691131,2203832,428
N. Jiang, S. Bai, Y. Xu, C. Xing, Z. Zhou, W. Wu. Online Inter-Camera Trajectory Association Exploiting Person Re-Identification and Camera Topology. In MM, 2018.
MTMC_ReID
10.
89.892.087.788.279.00.051,1231737,91186,958372772
Z. Zhang, J. Wu, X. Zhang, C. Zhang. Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project. In , 2017.
Tracker IDF1 IDP IDR MOTA MOTP FAF MT ML FP FN ID Sw. Frag
MFFusion
11. online method using public detections
84.986.683.480.975.60.111,0792381,023120,5413638,089
Anonymous submission
BIPCC
12. online method using public detections
70.183.660.459.478.70.0966523468,147361,672300801
E. Ristani, F. Solera, R. Zou, R. Cucchiara, C. Tomasi. Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking. In ECCV workshop on Benchmarking Multi-Target Tracking, 2016.
dirBIPCC
13. online method using public detections
70.083.260.459.078.70.1066523471,381361,673298799
Anonymous submission
PT_BIPCC
14. using public detections
71.284.861.459.378.70.0966623468,634361,589290783
A. Maksai, X. Wang, F. Fleuret, P. Fua. Non-Markovian Globally Consistent Multi-Object Tracking. In ICCV, 2017.
lx_b
15. online method using public detections
70.388.158.561.378.70.0464024726,845382,524246788
Anonymous submission
MTMCT_PA
16. using public detections
87.587.587.589.178.80.081,1651457,34357,848229376
Anonymous submission
MTMCT_sp
17. online method using public detections
91.492.990.090.478.20.051,1641234,05467,079214457
Anonymous submission
DeepCC
18.
89.291.786.787.577.10.051,1032937,28094,399202753
E. Ristani, C. Tomasi. Features for Multi-Target Multi-Camera Tracking and Re-Identification. In CVPR, 2018.
MTMCT_s
19. online method using public detections
91.392.889.890.678.30.041,1651132,31466,824178467
Anonymous submission
SAS_full
20. using public detections
84.089.479.276.076.00.099507266,783186,9741691,256
Anonymous submission
Tracker IDF1 IDP IDR MOTA MOTP FAF MT ML FP FN ID Sw. Frag
MTMC_basel
21.
91.391.890.990.778.70.061,1691444,49254,044153456
Anonymous submission

Multi-Camera

Tracker IDF1 IDP IDR
MTMCT_sp
1. online method using public detections
88.089.486.6
Anonymous submission
MTMC_basel
2.
87.487.887.0
Anonymous submission
MTMCT_s
3. online method using public detections
87.488.885.9
Anonymous submission
d_b_v13
4.
85.487.483.5
Anonymous submission
MTMC_ReID
5.
83.285.281.2
Z. Zhang, J. Wu, X. Zhang, C. Zhang. Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project. In , 2017.
DeepCC
6.
82.084.479.8
E. Ristani, C. Tomasi. Features for Multi-Target Multi-Camera Tracking and Re-Identification. In CVPR, 2018.
MTMC_ReIDp
7. using public detections
74.484.466.4
Z. Zhang, J. Wu, X. Zhang, C. Zhang. Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project. In , 2017.
MTMCT_PA
8. using public detections
72.472.572.4
Anonymous submission
TAREIDMTMC
9. online method
68.871.866.0
N. Jiang, S. Bai, Y. Xu, C. Xing, Z. Zhou, W. Wu. Online Inter-Camera Trajectory Association Exploiting Person Re-Identification and Camera Topology. In MM, 2018.
MYTRACKER
10. online method using public detections
65.471.160.6
K. Yoon, Y. Song, M. Jeon. Multiple hypothesis tracking algorithm for multi-target multi-camera tracking with disjoint views. In IET Image Processing, 2018.
Tracker IDF1 IDP IDR
MTMC_CDSC
11. using public detections
60.068.353.5
Y. Tesfaye, E. Zemene, A. Prati, M. Pelillo, M. Shah. Multi-Target Tracking in Multiple Non-Overlapping Cameras using Constrained Dominant Sets. In CoRR, 2017.
SAS_full
12. using public detections
59.963.856.5
Anonymous submission
lx_b
13. online method using public detections
58.072.648.2
Anonymous submission
BIPCC
14. online method using public detections
56.267.048.4
E. Ristani, F. Solera, R. Zou, R. Cucchiara, C. Tomasi. Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking. In ECCV workshop on Benchmarking Multi-Target Tracking, 2016.
MTMC___DS
15. using public detections
54.965.447.3
Anonymous submission
dirBIPCC
16. online method using public detections
52.162.045.0
Anonymous submission
SAS
17. using public detections
38.542.335.4
Submission id 177
PT_BIPCC
18. using public detections
34.941.630.1
A. Maksai, X. Wang, F. Fleuret, P. Fua. Non-Markovian Globally Consistent Multi-Object Tracking. In ICCV, 2017.
MOT_TBA
19. online method
27.828.826.8
Paper ID 648
MFFusion
20. online method using public detections
26.226.725.7
Anonymous submission
Tracker IDF1 IDP IDR
mtmct_hxq
21. online method
5.97.05.1
Anonymous submission

Hard Test Set

Single Camera (all)

Tracker IDF1 IDP IDR MOTA MOTP FAF MT ML FP FN ID Sw. Frag
mtmct_hxq
1. online method
49.058.242.466.072.70.084637822,099216,6183,6205,193
Anonymous submission
MTMC___DS
2. using public detections
62.679.451.657.375.30.0931410326,721276,2331,6724,946
Anonymous submission
MTMC_CDSC
3. using public detections
65.581.454.759.675.40.093489926,643260,0731,6375,024
Y. Tesfaye, E. Zemene, A. Prati, M. Pelillo, M. Shah. Multi-Target Tracking in Multiple Non-Overlapping Cameras using Constrained Dominant Sets. In CoRR, 2017.
MYTRACKER
4. online method using public detections
63.573.955.659.676.70.194008055,038231,5271,4681,801
K. Yoon, Y. Song, M. Jeon. Multiple hypothesis tracking algorithm for multi-target multi-camera tracking with disjoint views. In IET Image Processing, 2018.
SAS
5. using public detections
65.579.355.859.174.00.1437910239,576251,2569721,855
Submission id 177
d_b_v13
6.
82.390.775.476.276.70.095363824,319144,8139102,024
Anonymous submission
PT_BIPCC
7. using public detections
65.081.854.054.477.10.1433510440,978283,7046611,054
A. Maksai, X. Wang, F. Fleuret, P. Fua. Non-Markovian Globally Consistent Multi-Object Tracking. In ICCV, 2017.
MFFusion
8. online method using public detections
77.584.571.570.974.50.175244648,584158,1756606,556
Anonymous submission
dirBIPCC
9. online method using public detections
64.380.353.653.977.10.1633810245,472283,0146531,078
Anonymous submission
BIPCC
10. online method using public detections
64.581.253.554.677.10.1433810339,599283,3766521,073
E. Ristani, F. Solera, R. Zou, R. Cucchiara, C. Tomasi. Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking. In ECCV workshop on Benchmarking Multi-Target Tracking, 2016.
Tracker IDF1 IDP IDR MOTA MOTP FAF MT ML FP FN ID Sw. Frag
lx_b
11. online method using public detections
64.280.453.453.677.10.1633610745,370285,1926211,049
Anonymous submission
MTMC_ReIDp
12. using public detections
71.685.361.760.976.80.1437510440,732237,974572993
Z. Zhang, J. Wu, X. Zhang, C. Zhang. Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project. In , 2017.
TAREIDMTMC
13. online method
77.986.670.768.173.50.174984547,777179,0355412,074
N. Jiang, S. Bai, Y. Xu, C. Xing, Z. Zhou, W. Wu. Online Inter-Camera Trajectory Association Exploiting Person Re-Identification and Camera Topology. In MM, 2018.
MTMC_ReID
14.
81.289.474.574.776.60.115695730,297149,443521860
Z. Zhang, J. Wu, X. Zhang, C. Zhang. Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project. In , 2017.
MTMCT_PA
15. using public detections
80.384.976.277.576.60.156003243,666116,079469572
Anonymous submission
MTMCT_sp
16. online method using public detections
83.289.378.078.876.20.116063230,259120,511375580
Anonymous submission
MTMCT_s
17. online method using public detections
83.589.678.279.176.30.106073129,068119,967321512
Anonymous submission
MTMC_basel
18.
83.788.879.178.976.60.136143435,987114,104307602
Anonymous submission
SAS_full
19. using public detections
76.889.367.465.475.30.124508735,596210,639267977
Anonymous submission
DeepCC
20.
79.087.472.070.075.00.155246643,989170,104236777
E. Ristani, C. Tomasi. Features for Multi-Target Multi-Camera Tracking and Re-Identification. In CVPR, 2018.

Multi-Camera

Tracker IDF1 IDP IDR
d_b_v13
1.
78.586.471.8
Anonymous submission
MTMCT_s
2. online method using public detections
77.282.872.2
Anonymous submission
MTMCT_sp
3. online method using public detections
76.281.771.4
Anonymous submission
MTMC_basel
4.
75.480.071.3
Anonymous submission
MTMC_ReID
5.
74.081.467.8
Z. Zhang, J. Wu, X. Zhang, C. Zhang. Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project. In , 2017.
DeepCC
6.
68.575.962.4
E. Ristani, C. Tomasi. Features for Multi-Target Multi-Camera Tracking and Re-Identification. In CVPR, 2018.
MTMC_ReIDp
7. using public detections
65.678.156.5
Z. Zhang, J. Wu, X. Zhang, C. Zhang. Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project. In , 2017.
MTMCT_PA
8. using public detections
65.569.262.2
Anonymous submission
TAREIDMTMC
9. online method
61.268.055.5
N. Jiang, S. Bai, Y. Xu, C. Xing, Z. Zhou, W. Wu. Online Inter-Camera Trajectory Association Exploiting Person Re-Identification and Camera Topology. In MM, 2018.
SAS_full
10. using public detections
51.760.145.4
Anonymous submission
Tracker IDF1 IDP IDR
MTMC_CDSC
11. using public detections
50.963.242.6
Y. Tesfaye, E. Zemene, A. Prati, M. Pelillo, M. Shah. Multi-Target Tracking in Multiple Non-Overlapping Cameras using Constrained Dominant Sets. In CoRR, 2017.
MYTRACKER
12. online method using public detections
50.158.343.9
K. Yoon, Y. Song, M. Jeon. Multiple hypothesis tracking algorithm for multi-target multi-camera tracking with disjoint views. In IET Image Processing, 2018.
lx_b
13. online method using public detections
48.360.640.2
Anonymous submission
MTMC___DS
14. using public detections
47.660.439.3
Anonymous submission
BIPCC
15. online method using public detections
47.359.639.2
E. Ristani, F. Solera, R. Zou, R. Cucchiara, C. Tomasi. Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking. In ECCV workshop on Benchmarking Multi-Target Tracking, 2016.
dirBIPCC
16. online method using public detections
45.056.337.5
Anonymous submission
SAS
17. using public detections
33.040.028.1
Submission id 177
PT_BIPCC
18. using public detections
32.941.327.3
A. Maksai, X. Wang, F. Fleuret, P. Fua. Non-Markovian Globally Consistent Multi-Object Tracking. In ICCV, 2017.
MFFusion
19. online method using public detections
29.732.327.4
Anonymous submission
mtmct_hxq
20. online method
20.123.917.4
Anonymous submission


Evaluation Measures

Lower is better. Higher is better.
Measure Better Perfect Description
IDF1 higher 100 % ID F1 Score [1]. The ratio of correctly identified detections over the average number of ground-truth and computed detections.
IDP higher 100 % ID Precision [1]. Identification precision is the fraction of computed detections that are correctly identified.
IDR higher 100 % ID Recall [1]. Identification recall is the fraction of ground truth detections that are correctly identified.
MOTA higher 100 % Multiple Object Tracking Accuracy [2]. This measure combines three error sources: false positives, missed targets and identity switches.
MOTP higher 100 % Multiple Object Tracking Precision [2]. The misalignment between the annotated and the predicted bounding boxes.
FAF lower 0 The average number of false alarms per frame.
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).
ID Sw. lower 0 The total number of identity switches. Please note that we follow the stricter definition of identity switches as described in [3].
Frag lower 0 The total number of times a trajectory is fragmented (i.e. interrupted during tracking).

Legend

Symbol Description
online method 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.
using public detections This method used the provided detection set as input.
new This entry has been submitted or updated less than a week ago.

References:


[1] Ristani, E., Solera, F., Zou, R., Cucchiara, R. & Tomasi, C. Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking. In ECCV workshop on Benchmarking Multi-Target Tracking, 2016.
[2] Bernardin, K. & Stiefelhagen, R. Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics. Image and Video Processing, 2008(1):1-10, 2008.
[3] Li, Y., Huang, C. & Nevatia, R. 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.