Second LPT Challenge Case 3: Two-Pulse results

This page presents published results for the TP (Two-Pulse) case of the 2nd LPT Challenge Case 3. The link for result submission, as well as details about the test case and rules for result formatting are given there.

Tables can be ordered according to each of the quantities reported. Clicking on an algorithm name in a table will open a page gathering its result, together with information on the submitter.

Definition of performance metrics

Evaluation pertains to both particle localization, at the two pulse times t0 and t1, and estimation of the displacement vectors. For either particles or vectors, we count :

  • a True Positive (TP) if a ground truth (GT) particle is found in the neighborhood of a detection (maximum componentwise distance less than 1 voxel). For vectors, both detections should be TPs and associated to the same GT particle.
  • a False Negative (FN, a.k.a. missed particle) if there is no detection in the neighborhood of a GT particle. A FN vector is a GT vector that is not associated to a TP vector.
  • a False Positive (FP, a.k.a. ghost particle/vector) particle/vector when it is not a TP particle/vector.

Precision and Recall are derived quantities reflecting the detection performance, defined as:

 

Root-mean-square (rms) error on particle position or displacement are defined by only considering the TP within the result. 

In the tables, they are given in voxel, with a voxel size here equal to 528 µm; figures also show these errors in mm. Conversion from displacement to velocities can be done straightforwardly by considering the acquisition frequency, set to 30 Hz; for reference, the free-stream velocity is here equal to 0.6633 m/s.

Below the tables, we provide plots comparing some of these quantities among participants, as well as displacement error slices for a selected test point.

ppp: 0.005
Algorithm Sort descending Institution Prec. t0 Recall t0 #FN t0 #TP t0 #FP t0 Pos. rms error t0 X pos. rms error t0 Y pos. rms error t0 Z pos. rms error t0 Prec. t1 Recall t1 #TP t1 #FP t1 #FN t1 Pos. rms error t1 X pos. rms error t1 Y pos. rms error t1 Z pos. rms error t1 Vector Prec. Vector Recall #TP vectors #FP vectors #FN vectors Disp. rms error
TP-STB@DaVis LaVision GmbH 0.934 0.666 6609 13197 926 0.355 0.107 0.102 0.323 0.935 0.667 13203 920 6603 0.356 0.106 0.101 0.324 0.932 0.665 13169 954 6637 0.352
ppp: 0.03
Algorithm Sort descending Institution Prec. t0 Recall t0 #FN t0 #TP t0 #FP t0 Pos. rms error t0 X pos. rms error t0 Y pos. rms error t0 Z pos. rms error t0 Prec. t1 Recall t1 #TP t1 #FP t1 #FN t1 Pos. rms error t1 X pos. rms error t1 Y pos. rms error t1 Z pos. rms error t1 Vector Prec. Vector Recall #TP vectors #FP vectors #FN vectors Disp. rms error
ITE-PTV ONERA-CEA 0.883 0.889 13294 106281 14043 0.895 0.418 0.241 0.753 0.883 0.889 106256 14068 13319 0.895 0.419 0.242 0.753 0.878 0.884 105682 14642 13893 0.524
TP-STB@DaVis LaVision GmbH 0.939 0.839 19283 100292 6535 0.453 0.132 0.141 0.409 0.939 0.839 100330 6497 19245 0.45 0.132 0.137 0.407 0.937 0.837 100045 6782 19530 0.511
ppp: 0.045
Algorithm Sort descending Institution Prec. t0 Recall t0 #FN t0 #TP t0 #FP t0 Pos. rms error t0 X pos. rms error t0 Y pos. rms error t0 Z pos. rms error t0 Prec. t1 Recall t1 #TP t1 #FP t1 #FN t1 Pos. rms error t1 X pos. rms error t1 Y pos. rms error t1 Z pos. rms error t1 Vector Prec. Vector Recall #TP vectors #FP vectors #FN vectors Disp. rms error
TP-STB@DaVis LaVision GmbH 0.955 0.831 30349 148942 6953 0.481 0.139 0.142 0.438 0.955 0.831 148931 6964 30360 0.476 0.136 0.14 0.434 0.953 0.829 148564 7331 30727 0.538
ppp: 0.06
Algorithm Sort descending Institution Prec. t0 Recall t0 #FN t0 #TP t0 #FP t0 Pos. rms error t0 X pos. rms error t0 Y pos. rms error t0 Z pos. rms error t0 Prec. t1 Recall t1 #TP t1 #FP t1 #FN t1 Pos. rms error t1 X pos. rms error t1 Y pos. rms error t1 Z pos. rms error t1 Vector Prec. Vector Recall #TP vectors #FP vectors #FN vectors Disp. rms error
ITE-PTV ONERA-CEA 0.847 0.779 52955 186155 33635 0.933 0.421 0.265 0.789 0.847 0.778 186058 33732 53052 0.932 0.42 0.266 0.789 0.836 0.769 183816 35974 55294 0.664

2nd LPT Challenge case 3 TP results