Another test using exactly the same small blob rescale, but extended such that it takes 1000 frames to perform the circular movement. This results in the amount of movement being much much smaller between frames. This will give you an idea of how accurate the method can be...(click to zoom)Would you believe it eh.Here's the first few samples...0 0-0.01 0-0.024 -0.001-0.039 -0.001-0.057 -0.001-0.08 -0.002-0.106 -0.002-0.136 -0.002-0.167 -0.002-0.194 -0.004-0.214 -0.005-0.234 -0.005-0.251 -0.007-0.269 -0.008-0.289 -0.009-0.31 -0.009-0.337 -0.012-0.365 -0.014-0.402 -0.015-0.431 -0.018-0.455 -0.019-0.48 -0.02For this example, I'll quite confidently state that the 3rd decimal place is required, as accuracy under 0.01 pixels is clear. There are other sources of distortion, such as the little wobbles in the trace, which are caused by side-effects of the smoothing and upscaling when pixels cross certain boundaries. This reduces the *effective* accuracy. Can be quantified, by graphing the difference between *perfect* and the trace location, but not sure how much it matters.Now, obviously this level of accuracy does not directly apply to the video traces, as they contain all manner of other noise and distortion sources.Get SynthEyes (or equivalent)Get the video.Unfold it.Trace the NW corner in both frames (fields if you will)Export the traces.Open in excel.Save.Upload.Okay, new blob test variance results...Quite interesting. Shows the error across pixel boundaries (which makes sense), and the *drift* given circular movement (which is slightly surprising, but about a third of the pixel boundary scale, so may also make sense). Also shows variation in the oscillating frequency dependant upon rotation angle (which makes sense), and flattened, non-oscillating regions at 180 degree intervals (which again makes sense).A useful image, and should assist in defining trace accuracy considerably.Will look at the same thing with a square object, and then again with linear movement, rather than circular.Behaviour for square and linear movement is very similar to that of circular movement.So, from simple observation of the variance graph, I would suggest...a) The highest accuracy is attained when movement in parallel to the axis being traced.b) The highest accuracy is maintained when on-axis movement is < 1/4 perpendicular-to-axis movement. < 1/4 gradient. Within this margin for the example equates to within +/- 0.01 pixel accuracy.c) The highest *drift* is attained when movement is at maximum velocity.d) *drift* is recovered when velocity reduces.e) On such small regions (49 pixels) inter-pixel transitions can result in oscillating positional error of up to 0.06 pixels. It is expected that this will reduce as region size increases (and will be tested)f) Pixel transition error oscillation period is obviously related to movement velocity.g) Error does not appear to favour an axis.h) For pure on-axis movement, for a 7*7 region, minimum positional error lies within +/- 0.005 pixels.i) Interestin'