Updates the motion history image by a moving silhouette

mhi = cv.updateMotionHistory(silhouette, mhi, timestamp, duration)

Input

• silhouette Silhouette mask that has non-zero pixels where the motion occurs.
• mhi Input motion history image to be updated by the function (single-channel, 32-bit floating-point).
• timestamp Current time in milliseconds or other units.
• duration Maximal duration of the motion track in the same units as timestamp.

Output

• mhi Updated motion history image (single-channel, 32-bit floating-point).

The function updates the motion history image as follows:

            | timestamp  if silhouette(x,y) != 0
 mhi(x,y) = | 0          if silhouette(x,y) == 0 and mhi < (timestamp < duration)
            | mhi(x,y)   otherwise

That is, mhi pixels where the motion occurs are set to the current timestamp, while the pixels where the motion happened last time a long time ago are cleared.

The function, together with cv.calcMotionGradient and cv.calcGlobalOrientation, implements a motion templates technique described in [Davis97] and [Bradski00].

References

[Davis97]:

James W Davis and Aaron F Bobick. "The representation and recognition of human movement using temporal templates". In Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on, pages 928-934. IEEE, 1997.

[Bradski00]:

GR Bradski and J Davis. "Motion segmentation and pose recognition with motion history gradients". In Applications of Computer Vision, 2000, Fifth IEEE Workshop on., pages 238-244. IEEE, 2000.