Disparity Estimation Using Stereo Images With Different Focal Lengths

This study proposes a disparity estimation method for images captured by cameras with different focal lengths. Whereas a short focal length camera captures a close scene, a long focal length camera captures a far scene. The proposed method computes full disparity maps for both the close and far scenes. To achieve this, we introduce a stereo rectification method that works directly on images with different focal lengths and parameterizes the zoom levels between the two cameras. To evaluate the proposed method, we set up a stereo system with two cameras with different focal lengths and captured sequences of stereo images. In addition, we used KITTI, EISATS, and SceneFlow stereo datasets to simulate images with different focal lengths. Experimental results show that the proposed disparity estimation method successfully computed disparity maps for both near and far scenes, with significantly better performance than state-of-the-art monocular disparity estimation methods. Source code and experimental results are available online at https://github.com/comvisdinh/disparityestimation.