High resolution video mosaicing with global alignment

Marzotto, R.; Fusiello, Andrea; Murino, Vittorio

doi:10.1109/cvpr.2004.1315099

Cited by 65 publications

(62 citation statements)

References 14 publications

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“…For the global transformation estimation, a method which can consider the imaging geometry characteristics based on a graph method is applied. The graph method is divided into maximum spanning tree (MST) generation and reference plane determination phase (Marzotto et al, 2004;Kim and Kim, 2017). In MST generation, the proposed method applies TAR as weight to consider bias of tiepoint distribution.…”

Section: Proposed Methodsmentioning

confidence: 99%

Development of a Robust Image Mosaicking Method for Small Unmanned Aerial Vehicle

Kim

2017

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

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Commission VI, WG VI/4KEY WORDS: UAV, Image Mosaicking, Imaging Geometry Characteristics, Near-ortho mosaic ABSTRACT:In this paper, a tie-point based image mosaicking method considering imaging characteristics of small UAVs is proposed. Small UAVs can be characterized to have unstable flight trajectory and lower flight height. The proposed method considers the imaging characteristics in image transformation estimation and image blending process. For image transformation estimation, an optimal transformation model is variably applied by using tie-point area ratio. The optimal tie-point area ratio was about 0.3. Mosaicking error was largely decreased by using this tie-point area ratio. For image blending, a composite area minimization is introduced as a preceding step of image resampling. Composite areas of individual images were minimized by analyzing image overlaps between adjacent images. The proposed method was evaluated over flat area and urban area with highly overlapping multi-strip and inconsistently overlapping strip. Experiment results showed that the proposed method can reliably generate mosaics not only from UAV images acquired in good environment but also from extreme environment.

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Section: Proposed Methodsmentioning

confidence: 99%

Development of a Robust Image Mosaicking Method for Small Unmanned Aerial Vehicle

Kim

2017

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

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“…If we associate a weight (given by the measure of overlap) to each edge of an arbitrary graph (not necessarily a tree), then, among all possible trees that span the vertices of the graph, any one that collects the largest weights is called a maximum spanning tree (Marzotto et al, 2004). More than one may exist, for example when all the weights are equal; but the Kruskal's algorithm given in the subsection ''Kruskal's Algorithm'' under Appendix is sure to find one (Kruskal, 1956).…”

Section: Global Registration Strategymentioning

confidence: 99%

“…Photogrammetric approaches are now mature (Triggs et al, 1999). They posit that salient features can be identified in the tiles; then, the tiles are warped according to some deformation model (often a homography, sometimes combined with a lens-distortion model) to enforce that the coordinates of matched features do coincide (Kang et al, 2000;Marzotto et al, 2004). One challenging aspect is to determine which salient features do match which; another is to choose a measure of coincidence that is robust in the presence of mismatched features.…”

Section: Introductionmentioning

confidence: 99%

User‐friendly semiautomated assembly of accurate image mosaics in microscopy

Thévenaz

Unser

2006

Microscopy Res & Technique

252

202

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We present a semiautomated software solution to the problem of extending the lateral field of view of a classical microscope. The initial requirements are a set of overlapping images, along with their user-provided coarse mosaic. Our solution then refines this initial mosaic in a fully automatic fashion. We rely on a highly accurate registration engine to perform the pairwise registration of the individual images, and on an efficient strategy to minimize the amount of computations while maintaining the highest possible global quality. We describe these ingredients, which we make available as a free multiplatform user-friendly software package. We also highlight why and how the specific aspects of the present microscopy application differ from those encountered while creating more common mosaics such as panoramas. Finally, we present experimental results that illustrate and validate our method on a real biological sample. We conclude by showing that we are able to reach subpixel accuracy. Microsc. Res. Tech. 70:135-146, 2007. V

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“…Graph relationships on image sequences are frequently encountered in image mosaicking applications, e.g., [33], [34], [35]. However, in such cases, adjacent images can be assumed to have connecting edges, since they are closely-sampled frames of a smooth camera motion.…”

Section: Notation and Terminologymentioning

confidence: 99%

Calibrating Distributed Camera Networks

Devarajan¹,

Cheng²,

Radke

2008

Proc. IEEE

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Recent developments in wireless sensor networks have made feasible distributed camera networks, in which cameras and processing nodes may be spread over a wide geographical area, with no centralized processor and limited ability to communicate a large amount of information over long distances. This paper overviews distributed algorithms for the calibration of such camera networks-that is, the automatic estimation of each camera's position, orientation, and focal length. In particular, we discuss a decentralized method for obtaining the vision graph for a distributed camera network, in which each edge of the graph represents two cameras that image a sufficiently large part of the same environment. We next describe a distributed algorithm in which each camera performs a local, robust nonlinear optimization over the camera parameters and scene points of its vision graph neighbors to obtain an initial calibration estimate.We then show how a distributed inference algorithm based on belief propagation can refine the initial estimate to be both accurate and globally consistent.

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High resolution video mosaicing with global alignment

Cited by 65 publications

References 14 publications

Development of a Robust Image Mosaicking Method for Small Unmanned Aerial Vehicle

Development of a Robust Image Mosaicking Method for Small Unmanned Aerial Vehicle

User‐friendly semiautomated assembly of accurate image mosaics in microscopy

Calibrating Distributed Camera Networks

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