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From the sequence of images acquired, the relative change in pose of the robot is estimated using a phase correlation based method.
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Still, there is a correlation.
"mode=cpc" indicates that the cross coefficient is calculated using cross phase correlation.
The difference between the origin and centroid times was assumed to be the average of the time shifts, which were defined as the time deviation between the observed and synthetic waveforms estimated using phase correlation for a packet of P-waves.
Then, the angle θ 0 can be obtained by using phase correlation.
We estimate the rotation angle of test image to each image in dataset images using phase correlation technique.
Then, for each test image, we rotate it as the negative angle obtained using phase correlation technique to each dataset image.
We compensated the rotation angle of head or eye movement (gaze angle) in front of the retina fundus camera using phase correlation technique which was not mentioned in the counterpart methods.
Registration of these images is made in the adaptive polar transformed domain using phase correlation because it is very easy to find the number of change by phase correlation and registration can be made by realignment opposite to shifting in transformed domain.
For each rotation, we determined the optimal translation using phase correlation.
The relationship between impairment and gait-related variables and peak to peak swing phase knee amplitude and peak knee flexion velocity in preswing phase were assessed using a Pearson correlation.
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