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In every 3D measurement cycle a pair of images (left/right) are first captured using synchronised cameras and then transformed to a standard geometry (rectification) from which inter image pixel matching is performed and the resulting calculated disparity mapped to distance [14].
To examine the patterns of morphological evolution, we calculated disparity through time plots [ 26] for all brain structures and brain weight, using the package GEIGER [ 52] in R following Harmon et al. [ 26].
In this set of calculated disparity maps (Figure 10) the best performing approach is clearly SEMI [2] because both the close and distant objects within the scene are very differentiable.
In Appendix 1, Table 9, typical disparity values for each image are given, along with an example of the mean squared error for the calculated disparity maps.
where d is the calculated disparity map, dgt is the ground truth, P is the number of pixels, and S is the number of images in the set (e.g., for a single image S=1) for which the mean squared error is to be calculated for.
Similar(54)
This could be improved by taking into account already calculated disparities of the neighbouring pixels.
Sparse stereo matching methods do not calculate disparity at every pixel and are deployed for their low complexity or if only sparse data is needed.
The number of processed frames per second was then calculated assuming disparity range of 24.
The researchers calculated morphological disparity for seven major dinosaur groups using wide-ranging characteristics of the intricate skeletal structure of nearly 150 different species.
Then, we calculated the disparity level at the three studied ontogenetic stages within each trophic group.
Dense stereo matching methods calculate disparity at every pixel.
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