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Finally we present the estimates on the pooled sample using these methods to address missing distances.
Figure 6 (a) Error performance; (b) processing time with the number of multiple restart is constrained to 15, an empirical level at which both the error and missing distance tolerance performances are comparable for both approaches.
Figure 15 (a) Error performance; (b) processing time versus percentage of missing pairwise distances with uniform weighting and random missing distances.
Figure 17 (a) Error performance; (b) processing time versus percentage of missing pairwise distances with standard-deviation adjusted weighting and random missing distances.
Figure 4 (a) Error performance; (b) processing time versus percentage of missing pairwise distances using distances with added 0 mean and 5 m standard deviation Gaussian noise.
Figure 14 (a) Error performance; (b) processing time versus percentage of missing pairwise distances with uniform weighting and largest distances missing.
Human tracklet A1 is missing in (b) [62].
The results are shown in Figures 16 and 17. Figure 16 (a) Error performance; (b) processing time versus percentage of missing pairwise distances with standard-deviation adjusted weighting and largest distances missing.
This was then repeated with randomly chosen missing pairwise distances.
In (a), 50% of weak classifiers are missing, while in (b), 60% are missing.
Figure 21 shows the mapped coordinates of the nodes for different percentages of missing largest distances.
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