Temporal Lucas Kanade |

The temporally filtered Lucas-Kanade algorithm is another approach to extract optic flow over the temporal domain. While the combination of the Lucas-Kanade algorithm with a Kalman Filter included temporal filtering as a post-processing step the following approach includes the temporal filter directly in the estimation step. In the Lucas-Kanade algorithm the optic flow constraintis solved by weighted least-squares estimation over the spatial domain. Here we extend the estimation to the temporal domain leading to the following minimization problem: The solution to this minimization problem is given by equation 2. By choosing an exponential temporal weighting function (equation 3) we avoid to fully recompute
The properties of the temporal filtering are controlled by parameter α which must lie between 0 and 1 where larger values mean less filtering over the temporal domain.
Fleet, D., & Langley, K. (1995). Recursive filters for optical flow. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(1), 61-67
This method is available as an implementation for microcontroller as well as a generic C algorithm in the Library in |