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Minor doc fix.

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Ilya Lysenkov 2012-04-11 12:44:34 +00:00
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modules/video/doc/motion_analysis_and_object_tracking.rst
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@ -37,7 +37,7 @@ Calculates an optical flow for a sparse feature set using the iterative Lucas-Ka
* **OPTFLOW_USE_INITIAL_FLOW** Use initial estimations stored in ``nextPts`` . If the flag is not set, then ``prevPts`` is copied to ``nextPts`` and is considered as the initial estimate.
* **OPTFLOW_LK_GET_MIN_EIGENVALS** Use minimum eigen values as a error measure (see ``minEigThreshold`` description). If the flag is not set, then L1 norm between patches around the original and a moved point divided by number of pixels in a window is used as a error measure.
* **OPTFLOW_LK_GET_MIN_EIGENVALS** Use minimum eigen values as a error measure (see ``minEigThreshold`` description). If the flag is not set, then L1 distance between patches around the original and a moved point divided by number of pixels in a window is used as a error measure.
:param minEigThreshold: The algorithm computes a minimum eigen value of a 2x2 normal matrix of optical flow equations (this matrix is called a spatial gradient matrix in [Bouguet00]_) divided by number of pixels in a window. If this value is less then ``minEigThreshold`` then a corresponding feature is filtered out and its flow is not computed. So it allows to remove bad points earlier and speed up the computation.