Epipolar image generation on vehicle-based sequence images based on fundamental matrix

In the process of 3D information extraction using sequence images collected by vehicle-based mobile measurement system, epipolar image eliminates the vertical disparity of image pairs. Furthermore, it converts the search area of the correspondences from two-dimensional plane to one-dimensional line in dense matching, thus improving the matching accuracy and efficiency. However, unlike the nearly horizontal epipolar lines of aerial images, the epipolar lines of the vehicle-based sequence image pairs are distributed radially on the images, which makes it difficult for the vehicle-based sequence images to generate epipolar images. To solve the above problems, the fundamental matrix is used to determine the geometrical relation of the image pair to epipolar line. Then the epipolar image is generated by the fan-shaped circular epipolar model. First, high-precision correspondences are obtained by sparse matching for fundamental matrix estimation. Then we use the fundamental matrix to map the nuclear line quickly and determine the region of the epipolar line. At last, the image of the epipolar line area is resampled by bilinear interpolation in the direction of the epipolar line. Experiments were conducted using multiple sets of vehicle-based sequence images, and the average vertical disparity of the correspondences of the generated epipolar image is 0.63 pixels. The results show that the vertical disparity of the epipolar image generated by the proposed method is smaller, which verifies the correctness of the process.