Parallel optical flow estimation with capturing images in real time

Spatio-temporal differentiation method is one of the most effective methods of determining the velocity of moving objects owing to its low calculation cost, unnecessity of feature points. It is expected that the method can be used in real world. However, it is difficult to estimate optical flow in real time, because it must wait for 3 frames of image that the spatio-temporal differentiation method requires. Ideal program to estimate optical flow in real time should evaluate the velocity of moving objects each frame. In order to develop such program, we introduced a multi-core programming that captures image and evaluates the velocity of moving objects in parallel. In advance, when we measured time to estimate optical flow, it was found that the time for derivation of the eigenvalues accounts for most of the processing time. In order to reduce this time, we improved the method of calculating the eigenvalues. Moreover, to get more accurate optical flow, we compared pre-filters preferable to estimate optical flow.