A motion field generation algorithm using block matching of edge-flag histograms has been developed aiming at its application to motion recognition systems. Use of edge flags instead of pixel intensities has made the algorithm robust against illumination changes. In order to detect local motions of interest effectively, a new adaptive frame interval adjustment scheme has been introduced in which only the edge flags due to local motions present in the frame are accumulated and utilized in block matching. These edge flags are projected onto x and y axes to generate histograms and the motion in x and y directions are determined by histogram matching. As a result, the computational cost for best match search has been substantially reduced. A vector representation of the motion field is also proposed and has been applied to preliminary motion recognition experiments using Hidden Markov Models (HMMs). The advantage of the proposed method over the simple optical flow has been demonstrated.