Topic
Homography (computer vision)
About: Homography (computer vision) is a research topic. Over the lifetime, 2247 publications have been published within this topic receiving 51916 citations.
Papers published on a yearly basis
Papers
More filters
01 Oct 2019
TL;DR: This paper proposes the algorithm that accurately estimates pose by applying the direct method, which does not need to use a given template image, which enables landing in various environments.
Abstract: Autonomous landing has been studied on various types of landing targets. In particular, relative pose estimation between a moving landing target and a UAV is important for stable landing in various environments. Most of the studies on UAV landing for a moving landing target used templates given in advance and feature-based methods to estimate the relative pose between the UAV and the landing target. However, the feature-based methods are vulnerable to ambiguity due to the symmetric shape of the helipad or camera noise. In this paper, we propose the algorithm that accurately estimates pose by applying the direct method. The algorithm does not need to use a given template image, which enables landing in various environments. Since the algorithm does not use the feature-based method, there is no concern about the ambiguity. To evaluate the proposed algorithm, we collect our dataset and confirm that the proposed algorithm is more accurate than the feature-based method.
01 Dec 2008
TL;DR: This work addresses the problem of calibrating multiple cameras, with an overlapping field of view (FoV), observing pedestrians in a scene walking on an uneven terrain by automatically estimated the infinite homography between the cameras by using the special geometric information obtained from observing pedestrians.
Abstract: A calibrated camera is essential for computer vision systems. The prime reason being that such a camera acts as an angle measuring device. Once the camera is calibrated, applications like 3D reconstruction or metrology or other applications requiring real world information from the video sequences can be envisioned. Motivated by this, we address the problem of calibrating multiple cameras, with an overlapping field of view (FoV), observing pedestrians in a scene walking on an uneven terrain. This problem of calibration from an uneven terrain has so far not been addressed in the vision community. We automatically estimated the infinite homography between the cameras by using the special geometric information obtained from observing pedestrians. This homography provides constraints on the intrinsic (or interior) camera parameters while also enabling us to estimate the extrinsic (or exterior) camera parameters. We test the proposed method on real as well as synthetic data; encouraging results demonstrate the applicability of the proposed method.