MGRAPH: A Multi-Graph Homography Method to Generate Incremental Mosaics in Real Time From UAV Swarms

Ruiz, Juan Jesús; Caballero, Fernando; Merino, Luís

doi:10.1109/lra.2018.2844304

Cited by 15 publications

(25 citation statements)

References 16 publications

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“…From there, the same results as in Theorem 1 and Proposition 1 can be stated but with the innovation term Δ(Ĥ, p) given by (37) instead of (19). The proofs proceed identically to the proofs of Theorem 1 and Proposition 1 where the function  0 is chosen equal to ̊p(Ĥ, p) defined in (34) instead of (16). By definition, an observer is robust to outliers if the influence of any outlier is small enough to create any important offset.…”

Section: Outlier Rejection With M-estimator-like Nonlinear Observermentioning

confidence: 79%

“…Assume that the set  n of the measured directionsp i is consistent. Then, the aggregate cost ̊p(Ĥ, p) defined by (16) is non-degenerate and, consequently, (I,p) is a global minimum of the aggregate cost ̊p(Ĥ, p).…”

Section: Nonlinear Observer Designmentioning

confidence: 99%

“…The cost function (16) previously used for observer design is the sum of individual squared residuals…”

Section: Outlier Rejection With M-estimator-like Nonlinear Observermentioning

confidence: 99%

“…Navigation of robotic vehicles has been developed based on homography sequences [5][6][7][8][9] and one of the most successful visual servo control paradigms uses homographies [10,11]. Homography based methods are particularly well suited to navigation of unmanned aerial vehicles [12][13][14][15][16] where the ground terrain is viewed from a distance and the relief of surface features is negligible compared to the distance from the scene.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Feature‐based recursive observer design for homography estimation and its application to image stabilization

Hua

Trumpf

Hamel

et al. 2019

Asian Journal of Control

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This paper presents a new algorithm for online estimation of a sequence of homographies applicable to image sequences obtained from robotic vehicles equipped with vision sensors. The approach taken exploits the underlying Special Linear group structure of the set of homographies along with gyroscope measurements and direct point-feature correspondences between images to develop temporal filter for the homography estimate. Theoretical analysis and experimental results are provided to demonstrate the robustness of the proposed algorithm. The experimental results show excellent performance and robustness even in the case of very fast camera motions (relative to frame rate) and severe occlusions.

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Section: Outlier Rejection With M-estimator-like Nonlinear Observermentioning

confidence: 79%

Section: Nonlinear Observer Designmentioning

confidence: 99%

“…The cost function (16) previously used for observer design is the sum of individual squared residuals…”

Section: Outlier Rejection With M-estimator-like Nonlinear Observermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Feature‐based recursive observer design for homography estimation and its application to image stabilization

Hua

Trumpf

Hamel

et al. 2019

Asian Journal of Control

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“…Applications for swarm mapping have included surveillance missions, search and rescue operations, weed mapping, and oil spill mapping (Albani, Nardi, & Trianni, ; Howden, ; Nigam, Bieniawski, Kroo, & Vian, ; Odonkor, Ball, & Chowdhury, ; Pitre, Li, & Delbalzo, ; San Juan et al, ). However, studies remain focussed on using simulations to test either algorithms (Almeida, Hildmann, & Solmaz, ; Chen, Ye, & Li, ; Yang, Ji, Yang, Li, & Li, ; Zhao et al, ) or data processing techniques (Casbeer, Kingston, Beard, & McLain, ; Ruiz, Caballero, & Merino, ). Despite the lack of real‐world testing due to physical and legal constraints, swarm technology may enable rapid acquisition of data for river corridor applications on unprecedented scales.…”

Section: Future Directionsmentioning

confidence: 99%

Remote sensing of river corridors: A review of current trends and future directions

Tomsett

Leyland

2019

River Research & Apps

112

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River corridors play a crucial environmental, economic, and societal role yet also represent one of the world's most dangerous natural hazards, making monitoring imperative to improve our understanding and to protect people. Remote sensing offers a rapidly growing suite of methods by which river corridor monitoring can be performed efficiently, at a range of scales and in difficult environmental conditions. This paper aims to evaluate the current state and assess the potential future of river corridor monitoring, whilst highlighting areas that require further investigation. We initially review established methods that are used to undertake river corridor monitoring, framed by the context and scales upon which they are applied. Subsequently, we review cutting edge technologies that are being developed and focussed around unmanned aerial vehicle and multisensor system advances. We also "horizon scan" for future methods that may become increasingly prominent in research and management, citing examples from within and outside of the fluvial domain. Through review of the literature, it has become apparent that the main gap in fluvial remote sensing lies in the trade-off between resolution and scales. However, prioritising process measurements and simultaneous multisensor data collection is likely to offer a bigger advance in understanding than purely from better surveying methods alone. Challenges regarding the legal deployment of more complex systems, as well as effectively disseminating data into the science community, are amongst those that we propose need addressing. However, the plethora of methods currently available means that researchers and monitoring agencies will be able to identify suitable techniques for their needs.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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HighStitch: High Altitude Georeferenced Aerial Images Stitching for Rocking Telephoto Lens

Zhao

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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MGRAPH: A Multi-Graph Homography Method to Generate Incremental Mosaics in Real Time From UAV Swarms

Cited by 15 publications

References 16 publications

Feature‐based recursive observer design for homography estimation and its application to image stabilization

Feature‐based recursive observer design for homography estimation and its application to image stabilization

Remote sensing of river corridors: A review of current trends and future directions

HighStitch: High Altitude Georeferenced Aerial Images Stitching for Rocking Telephoto Lens

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