Extrinsic Parameters Calibration Method of Cameras with Non-Overlapping Fields of View in Airborne Remote Sensing

Yin, Lei; Wang, Xiangjun; Ni, Yubo; Zhou, Kai; Zhang, Jilong

doi:10.3390/rs10081298

Cited by 17 publications

(8 citation statements)

References 27 publications

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“…They could calculate the relative pose between camera, plane and projector. For non-overlapping cameras in aero photogrammetry, Yin et al [27] introduced a novel marker-based method based on multiple chessboard targets. Sufficient equations can be obtained to solve the extrinsic parameters by moving camera at multiple positions.…”

Section: Related Workmentioning

confidence: 99%

UAV-Assisted Wide Area Multi-Camera Space Alignment Based on Spatiotemporal Feature Map

Jing

Xie

et al. 2021

Remote Sensing

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In this paper, we investigate the problem of aligning multiple deployed camera into one united coordinate system for cross-camera information sharing and intercommunication. However, the difficulty is greatly increased when faced with large-scale scene under chaotic camera deployment. To address this problem, we propose a UAV-assisted wide area multi-camera space alignment approach based on spatiotemporal feature map. It employs the great global perception of Unmanned Aerial Vehicles (UAVs) to meet the challenge from wide-range environment. Concretely, we first present a novel spatiotemporal feature map construction approach to represent the input aerial and ground monitoring data. In this way, the motion consistency across view is well mined to overcome the great perspective gap between the UAV and ground cameras. To obtain the corresponding relationship between their pixels, we propose a cross-view spatiotemporal matching strategy. Through solving relative relationship with the above air-to-ground point correspondences, all ground cameras can be aligned into one surveillance space. The proposed approach was evaluated in both simulation and real environments qualitatively and quantitatively. Extensive experimental results demonstrate that our system can successfully align all ground cameras with very small pixel error. Additionally, the comparisons with other works on different test situations also verify its superior performance.

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Section: Related Workmentioning

confidence: 99%

UAV-Assisted Wide Area Multi-Camera Space Alignment Based on Spatiotemporal Feature Map

Jing

Xie

et al. 2021

Remote Sensing

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“…Suppose that during the time period δt, the point on the surface of the object moves by δr 0 = v 0 δt, and then the point p i on the corresponding image moves by δr i = v i δt. Therefore, the speed of motion of the points is defined as v 0 = dr 0 dtv i = dr i dt (1) where the relationship between r 0 and r i can be determined by the perspective projection equation 1…”

Section: ) Motion Fieldmentioning

confidence: 99%

“…Image feature matching is one of the basic research directions in the fields of close range photogrammetry and computer vision. It has been widely used in camera calibration [1], 3D reconstruction [2], and pattern recognition [3]. The usual feature matching algorithm follows a two-step strategy [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Image Feature Matching Via Parallax Mapping for Close Range Photogrammetric Application

2020

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Image feature matching is an important step in close range photogrammetric applications, and implementing a fast, accurate and robust feature-based image matching technique is a challenging task. To solve the problems of traditional image feature matching algorithms, such as their low accuracy and long processing time, we present a parallax mapping-based matching (PMM) method that is able to improve the computation efficiency, accuracy and robustness of feature-based image matching for close range photogrammetric applications. First, the disparity of the initial corresponding points is calculated, and the mismatches are initially removed via local disparity clustering. Then, the local coordinates of the matching points are constrained by an image division grid. To ensure the correctness of the matching points, the fast polynomial transform is used for as a quadratic constraint. The method can extract high accuracy matching points from the original coarse matching points with low accuracy, and also preserve the true matching points to the greatest extent. Using a variety of experimental datasets and current mainstream feature extraction algorithms, we designed and compared commonly used feature-based image matching algorithms. The experimental results show that the proposed method is simple but effective, can meet the real-time calculation requirements, and outperforms the current state-of-the-art methods. INDEX TERMS Image matching, rejecting mismatches, motion consistency, parallax mapping, polynomial.

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“…Thus motivated, this paper is a preliminary study as to whether, and under which conditions, an extended approach based on a set of unordered coplanar chessboards might, in principle, simulate an (infeasibly large) single chessboard, to effectively accommodate longer focusing distances or wider fields of view. Multiple (non-coplanar) or 3D chessboards have already been exploited for camera-to-camera, camera-to-range sensor or multiple depth camera automatic calibration (Geiger et al, 2012;Fuersattel et al, 2017;Yin et al, 2018;Fu et al, 2019;Liu et al 2019). Yet, to the best of our knowledge, the particular use of multiple coplanar chessboards for camera calibration has not been investigated.…”

Section: Introductionmentioning

confidence: 99%

Camera Calibration Using Multiple Unordered Coplanar Chessboards

Γραμματικόπουλος

Adam

Petsa

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The now widely available and highly popular among non-expert users, particularly in the context of UAV photogrammetry, Structure-from-Motion (SfM) pipelines have also further renewed the interest in the issue of automatic camera calibration. The well-documented requirements for robust self-calibration cannot be always met, e.g. due to restrictions in time and cost, absence of ground control and image tilt, terrain morphology, unsuitable flight configuration etc.; hence, camera pre-calibration is frequently recommended. In this context, users often resort to flexible, user-friendly tools for camera calibration based on 2D coded patterns (primarily ordinary chessboards). Yet, the physical size of such patterns poses obvious limitations. This paper discusses the alternative of extending the size of the calibration object by using multiple unordered coplanar chessboards, which might accommodate much larger imaging distances. This is done initially by a detailed simulation to show that – in terms of geometry – this could be a viable alternative to single patterns. A first algorithmic implementation is then laid out, and results from real multi-pattern configurations, both ordered and unordered, are successfully compared. However, aspects of the proposed approach need to be further studied for its reliable practical employment.

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Extrinsic Parameters Calibration Method of Cameras with Non-Overlapping Fields of View in Airborne Remote Sensing

Cited by 17 publications

References 27 publications

UAV-Assisted Wide Area Multi-Camera Space Alignment Based on Spatiotemporal Feature Map

UAV-Assisted Wide Area Multi-Camera Space Alignment Based on Spatiotemporal Feature Map

Image Feature Matching Via Parallax Mapping for Close Range Photogrammetric Application

Camera Calibration Using Multiple Unordered Coplanar Chessboards

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