Viewpoint Estimation for Visual Target Navigation by Leveraging Keypoint Detection

In this paper, we tackle the problem of visual target navigation which is a crucial task for embodied AI. Given a target observation and an initial observation, we extract keypoints using an off-the-shelf keypoint detection model. Then we find sparse keypoint correspondences and estimate the relative camera pose with the PnP algorithm to reach the viewpoint for the target observation. Compared to conventional approaches, our method is faster, and more robust to scene changes and occlusions. We collected a 3D scan dataset in a university building and the proposed method is verified using the dataset.