Table 2.

Analysis of the computational cost (in minutes)

Analysis of the computational cost (in minutes)
Operation	Time-Point	Plant 1	Plant 2	Plant 3	Plant 4	Plant 5	Plant 6
		T0	0.62	0.64	0.71	0.70	0.61	0.62
		T1	0.64	0.62	0.57	0.51	0.55	0.81
Segmentation
	T2	0.71	0.69	0.52	0.68	0.65	0.60
	T3	0.68	0.62	0.67	0.80	0.71	0.81
	T0	0.075	0.065	0.082	0.073	0.074	0.078
		T1	0.067	0.066	0.075	0.062	0.074	0.074
Data extraction
	T2	0.072	0.068	0.061	0.063	0.068	0.067
	T3	0.073	0.072	0.071	0.076	0.071	0.071
Temporal organs matching		2.21	2.51	2.16	2.01	2.05	2.12
Complete mesh analysis		4.97	5.19	4.65	4.77	4.67	5.06

For the sake of consistency in the analysis of the CPU time (number of CPU cycles elapsed between the beginning and the end of an operation) required to run each step of the pipeline, we initially decimated all the plant meshes to 70000 triangles. The programs were run on a computer equipped with a processor Intel Core 2 Duo E8300 (2.83GHz). The segmentation steps were executed successively (non-threaded pipeline) and the results were obtained in less than 1 minute (< 50s) for every plant mesh. The data extraction steps were also executed successively, and the processing time required was negligible (< 0.082 min / < 5s per plant and per time-point). The CPU time required to run the plant parts matching for four time-points oscillated around 2 minutes (depending on the number of leaves). Operations of alignment and matching were executed successively. Note that the temporal pipeline includes the data extraction algorithm, as the plant data are required by the temporal pipeline. Finally the CPU time required to run the full mesh processing pipeline was around 5 minutes per plant. For a given plant, the segmentation of the different meshes were executed in parallel (4 time-points = 4 plant mesh segmentations) and followed by a serial temporal analysis.