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I am trying to understand the LK algorithm and it returns me a list of points in float. How can I visualise these list of points? My expectation was that they are integer values basically pixel locations on the image, where a prospective goodFeaturesToTrack was found. Also, this question is related directly to the goodFeaturesToTrack function, where the function returns a feature array in float. How can I actually visualise this intuitively?

I am trying to understand the LK algorithm and it returns me a list of points in float. How can I visualise these list of points? My expectation was that they are integer values basically pixel locations on the image, a location where a prospective goodFeaturesToTrack was found. Also, this question is related directly to the goodFeaturesToTrack function, where the function returns a feature array in float. How can I actually visualise this intuitively?

I am trying to understand the prev_pts and next_pts in the LK algorithm and it returns me a list of points in float. algorithm. How can I visualise these list of points? My expectation was that they are integer values basically pixel locations on the image, a location where a prospective goodFeaturesToTrack was found. Also, this question is related directly to the goodFeaturesToTrack function, where the function returns a feature array in float. How can I actually visualise this intuitively?

I am trying to understand the prev_pts and next_pts in the LK algorithm. How can I visualise these list of points? points intuitively? My expectation was that they are integer values basically pixel locations on the image, a location where a prospective goodFeaturesToTrack was found. Also, this question is related directly to the goodFeaturesToTrack function, where the function returns a feature array in float. How can I actually visualise this intuitively?