A new approach for automatic selection and transfer of corresponding image points in digital video image sequences

We present a new approach for automatic selection and transfer of corresponding image points in digital video (DV) image sequences. This approach utilizes and extends some well-known techniques and theories (e.g. the optical flow theory) as well as a designed simple error-detection mechanism to achieve a much better efficiency than the well-known Lucas-Kanade optical flow estimation (LK) method. Our test results use the SONY DCR-PC115 DV image sequences and show that the trackable range of 3-4 pixels in the LK method can apparently be enlarged to 30 pixels in this new approach. The proposed error-detection mechanism simply utilizes the average gradient, normalized cross-correlation, and a simple image registration aided by least squares adjustment. Test results show that it can efficiently detect and delete wrong tracked points, and thus improve the quality of point transfer, and provide accurate coordinates of a large number of corresponding image points in DV image sequences. This work aims at high precision automatic image triangulation for the automatic real-time mobile mapping vehicle system (MMVS). Some future works need to be done.