Motion here is measured as the mean correlation between the luminance values of all pixels in successive frames where all of those frames occur within a given shot.
Optical flow, a biologically inspired approach for obstacle avoidance, is the pattern of apparent motion of pixels in successive image frames [34].
Distance traveled measured in pixels between successive frames was computed, and converted into centimeters using known landmark distances in the video frame.
For each frame, the distance of the light/dark interface from the start of the line was determined, along with the mean squared difference in intensity between successive frames of the pixels along the line (Fig. 2).
Only those particles whose orientations and centers had changed their orientation and position by less than 2° and 2 pixels between successive cycles were retained for the next reconstruction.
We show that the use of statistical finite mixture models with groups of original pixel-scale measurements, at successive spatial scales, offers improved pixel-wise classification accuracy as compared to the commonly used technique of label aggregation.
These facets are tracked in each successive image with sub-pixel accuracy.
The changes in intensity between successive frames for each pixel within these average image frames were calculated according to Eq. 13.
The mean change in image intensity across images was calculated by taking the average of the absolute differences in gray value at each pixel for successive pairs of images within a block.
Similarity was measured with an algorithm that consisted of ROI registration (in addition to stack registration), Gabor filtering, local thresholding, and an exclusive-nor (XNOR) operation on every pixel of successive OCA images.
